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Climate Change 2007 Mitigation of Climate Change The Intergovernmental Panel on Climate Change (IPCC) was set up jointly by the World Meteorological Organization and the United Nations Environment Programme to provide an authoritative international statement of scientific understanding of climate change. The IPCC’s periodic assessments of the causes, impacts and possible response strategies to climate change are the most comprehensive and up-to-date reports available on the subject, and form the standard reference for all concerned with climate change in academia, government and industry worldwide. Through three working groups, many hundreds of international experts assess climate change in this Fourth Assessment Report. The Report consists of three main volumes under the umbrella title Climate Change 2007, all available from Cambridge University Press: Climate Change 2007 – The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the IPCC (ISBN 978 0521 88009-1 Hardback; 978 0521 70596-7 Paperback) Climate Change 2007 – Impacts, Adaptation and Vulnerability Contribution of Working Group II to the Fourth Assessment Report of the IPCC (978 0521 88010-7 Hardback; 978 0521 70597-4 Paperback) Climate Change 2007 – Mitigation of Climate Change Contribution of Working Group III to the Fourth Assessment Report of the IPCC (978 0521 88011-4 Hardback; 978 0521 70598-1 Paperback)
Climate Change 2007 – Mitigation of Climate Change aims to answer essentially five questions relevant to policymaking worldwide: • What can we do to reduce or avoid the threats of climate change? • What are the costs of these actions and how do they relate to the costs of inaction? • How much time is available to realise the drastic reductions needed to stabilise greenhouse gas concentrations in the atmosphere? • What are the policy actions that can overcome the barriers to implementation? • How can climate mitigation policy be aligned with sustainable development policies? This latest assessment of the IPCC provides a comprehensive, state-of-the-art and worldwide overview of scientific knowledge related to the mitigation of climate change. It includes a detailed assessment of costs and potentials of mitigation technologies and practices, implementation barriers, and policy options for the sectors: energy supply, transport, buildings, industry, agriculture, forestry and waste management. It links sustainable development policies with climate change practices. This volume will again be the standard reference for all those concerned with climate change, including students and researchers, analysts and decision-makers in governments and the private sector.
From reviews of the Third Assessment Report – Climate Change 2001: ‘The detail is truly amazing … invaluable works of reference … no reference or science library should be without a set [of the IPCC volumes] … unreservedly recommended to all readers.’ Journal of Meteorology ‘This well-edited set of three volumes will surely be the standard reference for nearly all arguments related with global warming and climate change in the next years. It should not be missing in the libraries of atmospheric and climate research institutes and those administrative and political institutions which have to deal with global change and sustainable development.’ Meteorologische Zeitschrift ‘… likely to remain a vital reference work until further research renders the details outdated by the time of the next survey … another significant step forward in the understanding of the likely impacts of climate change on a global scale.’ International Journal of Climatology ‘The IPCC has conducted what is arguably the largest, most comprehensive and transparent study ever undertaken by mankind … The result is a work of substance and authority, which only the foolish would deride.’ Wind Engineering ‘… the weight of evidence presented, the authority that IPCC commands and the breadth of view can hardly fail to impress and earn respect. Each of the volumes is essentially a remarkable work of reference, containing a plethora of information and copious bibliographies. There can be few natural scientists who will not want to have at least one of these volumes to hand on their bookshelves, at least until further research renders the details outdated by the time of the next survey.’ The Holocene ‘The subject is explored in great depth and should prove valuable to policy makers, researchers, analysts, and students.’ American Meteorological Society
From reviews of the Second Assessment Report – Climate Change 1995: ‘ … essential reading for anyone interested in global environmental change, either past, present or future. … These volumes have a deservedly high reputation’ Geological Magazine ‘… a tremendous achievement of coordinating the contributons of well over a thousand individuals to produce an authoritative, state-of-the-art review which will be of great value to decision-makers and the scientific community at large … an indispensable reference.’ International Journal of Climatology ‘... a wealth of clear, well-organized information that is all in one place ... there is much to applaud.’ Environment International
Climate Change 2007 Mitigation of Climate Change
Edited by
Bert Metz
Ogunlade Davidson
Co-chair Working Group III Netherlands Environmental Assessment Agency
Co-chair Working Group III University of Sierra Leone
Peter Bosch
Rutu Dave
Leo Meyer
Technical Support Unit IPCC Working Group III Netherlands Environmental Assessment Agency
Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change Published for the Intergovernmental Panel on Climate Change
CAMBRIDGE UNIVERSITY PRESS
Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521880114 © Intergovernmental Panel on Climate Change 2007 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published in print format 2007 eBook (EBL) ISBN-13 978-0-511-36651-2 ISBN-10 0-511-36651-5 eBook (EBL) ISBN-13 ISBN-10
hardback 978-0-521-88011-4 hardback 0-521-88011-4
ISBN-13 ISBN-10
paperback 978-0-521-70598-1 paperback 0-521-70598-3
Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.
Contents Foreword
vii
Preface
ix
Summary for Policymakers
1
Technical Summary
25 95
1
Introduction
2
Framing issues
117
3
Issues related to mitigation in the long term context
169
4
Energy supply
251
5
Transport and its infrastructure
323
6
Residential and commercial buildings
387
7
Industry
447
8
Agriculture
497
9
Forestry
541
10 Waste management
585
11 Mitigation from a cross sectoral perspective
619
12 Sustainable Development and mitigation
691
13 Policies, instruments and co-operative agreements
745
Annex I:
Glossary
809
Annex II: Acronyms, abbreviations and chemical compounds
823
Annex III: List of contributors
827
Annex IV: List of reviewers
833
Index
841
Foreword “Climate Change 2007 – Mitigation of Climate Change”, the third volume of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), provides an in-depth analysis of the costs and benefits of different approaches to mitigating and avoiding climate change.
The preparation of an IPCC Assessment Report is a complex and absorbing process. We would like to express our gratitude to the Technical Support Unit for its massive organizational efforts. We would also like to thank the IPCC Secretariat for its dedication to the efficient completion of the report.
In the first two volumes of the “Climate Change 2007” Assessment Report, the IPCC analyses the physical science basis of climate change and the expected consequences for natural and human systems. The third volume of the report presents an analysis of costs, policies and technologies that could be used to limit and/or prevent emissions of greenhouse gases, along with a range of activities to remove these gases from the atmosphere. It recognizes that a portfolio of adaptation and mitigation actions is required to reduce the risks of climate change. It also has broadened the assessment to include the relationship between sustainable development and climate change mitigation.
We express our appreciation to the Government of the Netherlands, which hosted the Technical Support Unit; the Government of Thailand, which hosted the plenary session for the approval of the report; the Governments of China, Germany, New Zealand and Peru, which hosted the Lead Authors’ meetings; and to all the countries that contributed to IPCC work through financial and logistic support.
At regular intervals of five or six years, the IPCC presents comprehensive scientific reports on climate change that assess the existing scientific, technical and socioeconomic literature. The rigorous multi-stage review process of the reports, the broad and geographically-balanced participation of experts from all relevant fields of knowledge and the thousands of comments taken into account guarantee a transparent and unbiased result. As an intergovernmental body established by the World Meteorological Organization and the United Nations Environment Programme, the IPCC has the responsibility of providing policymakers with objective scientific and technical findings that are policy relevant but not policy prescriptive. This is especially evident in the Mitigation report, which presents tools that governments can consider and implement in their domestic policies and measures in the framework of international agreements. Hundreds of authors contributed to the preparation of this report. They come from different backgrounds and possess a wide range of expertise, from emissions modelling to economics, from policies to technologies. They all dedicated a large part of their valuable time to the preparation of the report. We would like to thank them all, in particular the 168 Coordinating Lead Authors and Lead Authors most closely engaged in the process.
We wish to sincerely thank Dr Rajendra K. Pachauri, Chairman of the IPCC, for his steady and discreet guidance and to express our deep gratitude to Drs Ogunlade Davidson and Bert Metz, Co-Chairs of Working Group III, who successfully led their team with positive, efficient and constructive direction.
M. Jarraud Secretary General World Meteorological Organization
A. Steiner Executive Director United Nations Environment Programme
vii
Preface The Fourth Assessment Report of IPCC Working Group III, “Mitigation of Climate Change”, aims to answer essentially five questions relevant to policymakers worldwide: • What can we do to reduce or avoid climate change? • What are the costs of these actions and how do they relate to the costs of inaction? • How much time is available to realise the drastic reductions needed to stabilise greenhouse gas concentrations in the atmosphere? • What are the policy actions that can overcome the barriers to implementation? • How can climate mitigation policy be aligned with sustainable development policies?
The Summary for Policymakers was approved line by line, and the main report and Technical Summary were accepted at the 9th session of the IPCC Working Group III held in Bangkok, Thailand from 30 April to 4 May 2007.
A description of mitigation options for the various societal sectors that contribute to emissions forms the core of this report. Seven chapters cover mitigation options in energy supply, transport, buildings, industry, agriculture, forestry and waste management, with one additional chapter dealing with the cross-sectoral issues. The authors have provided the reader with an up-to-date overview of the characteristics of the various sectors, the mitigation measures that could be employed, the costs and specific barriers, and the policy implementation issues. In addition, estimates are given of the overall mitigation potential and costs per sector, and for the world as a whole. The report combines information from bottom-up technological studies with results of topdown modelling exercises. Mitigation measures for the short term are placed in the long-term perspective of realising stabilisation of global average temperatures. This provides policy-relevant information on the relation between the stringency of stabilisation targets and the timing and amount of mitigation necessary. Policies and measures to achieve mitigation action, both at national and international levels, are covered in chapter 13; this is additional to what is included in the sector chapters. The link between climate change mitigation, adaptation and sustainable development has been further elaborated in the relevant chapters of the report, with one chapter presenting an overview of the connections between sustainable development and climate change mitigation.
We are particularly grateful to the governments of Germany, Peru, China and New Zealand, who, in collaboration with local institutions, hosted the crucial lead author meetings in Leipzig (October 2004), Lima (June 2005), Beijing (February 2006) and Christchurch (October 2006).
The process After two scoping meetings to establish possible content, the formal assessment production process got underway in 2003 with the approval of the report outline by the IPCC at the Panel’s 21st session. Soon after this, an author team of 168 lead authors (55 from developing countries, 5 from EIT countries and 108 from OECD countries) and 85 contributing authors was formed by the Working Group III Bureau, based on nominations from governments and international organisations. Thirty-six per cent of the lead authors came from developing countries and countries with economies in transition. The IPCC review procedure was followed, in which drafts produced by the authors were subject to two reviews. Thousands of comments from a total of 485 expert reviewers, and governments and international organisations were processed. The processing into new drafts was overseen by two review editors per chapter, who ensured that all substantive comments received appropriate consideration.
Acknowledgements Production of this report was a major enterprise, in which many people all around the world delivered a wide variety of contributions. This input could not have been made without the generous support from the governments and institutions involved, which enabled the authors, review editors and reviewers to participate in this process. To them, our thanks.
Various countries and institutions supported expert meetings and stakeholder consultations that have contributed to the depth and scope of the report, namely: • Adaptation, mitigation and sustainable development in La Réunion (supported by the government of France) • Emissions scenarios in Washington DC (supported by the US Government) • Input by industry representatives in Tokyo (supported by the Japanese government) and Cape Town, South Africa (co-sponsored by ESKOM), and • Input from environmental NGOs, intergovernmental organisations, research organisations and members of the International Energy Agency and its technology network in Paris (in cooperation with the IEA). Throughout the process, the Working Group III Bureau – consisting of Ramón Pichs Madruga (Cuba), R.T.M. Sutamihardja (Indonesia), Hans Larsen (Denmark), (up to May 2005), Olav Hohmeyer (Germany, from June 2005), Eduardo Calvo (Peru), Ziad H.Abu-Ghararah (Saudi Arabia, up to September 2005), and Taha M. Zatari (Saudi Arabia, after September 2005), Ismail A.R. Elgizouli (Sudan) – delivered constructive support and continuous encouragement. The success of this report is, however, fully based on the expertise and enthusiasm of the author team for which we are grateful. We would also like to express our appreciation of the expert reviewer inputs. Without their comments, the report would not have achieved its current quality level. Our review editors had a similar critical role in supporting the author team in dealing with the comments. The assessment process was supported by the Technical Support Unit, financed by the government of the Netherlands. The following persons provided support, advice and coordination: Leo Meyer, Peter Bosch, Rutu Dave, Monique Hoogwijk, Thelma van den Brink, Anita Meier, Sander Brinkman, Heleen de Coninck, Bertjan Heij, David de ix
Jager, John Kessels, Eveline Trines, Manuela Loos (editing support), Martin Middelburg (layout), Rob Puijk (webmaster), Ruth de Wijs (coordination of copyediting), Marilyn Anderson (index) and many more from the secretariats of MNP and ECN in the Netherlands. Finally, we would like to thank the IPCC secretariat in Geneva in the persons of Renate Christ (Secretary of the IPCC), Jian Liu, Carola Saibante, Rudie Bourgeois, Annie Courtin and Joelle Fernandez for their continuous support throughout the process.
Bert Metz Ogunlade Davidson Co-chairs, IPCC Working Group III
This report is dedicated to
Gerhard Petschel-Held, Germany Lead Author in Chapter 12 Gerhard Petschel-Held died unexpectedly on September 9, 2005, at the age of 41 years. He worked at the Potsdam Institute for Climate Impact Research as head of the department Integrated Systems Analysis. He was an excellent scientist and a wonderful person to work with. Based on his scientific credentials and his capacity to integrate, Gerhard Petschel-Held played a key role in several international research networks. He believed strongly in the communication of scientific knowledge to a wider public, and to improve the world with the help of science.
x
Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
Summary for Policymakers This Summary for Policymakers was formally approved at the 9th Session of Working Group III of the IPCC, Bangkok, Thailand. 30 April - 4 May 2007
Drafting authors: Terry Barker, Igor Bashmakov, Lenny Bernstein, Jean Bogner, Peter Bosch, Rutu Dave, Ogunlade Davidson, Brian Fisher, Michael Grubb, Sujata Gupta, Kirsten Halsnaes, BertJan Heij, Suzana Kahn Ribeiro, Shigeki Kobayashi, Mark Levine, Daniel Martino, Omar Masera Cerutti, Bert Metz, Leo Meyer, Gert-Jan Nabuurs, Adil Najam, Nebojsa Nakicenovic, Hans Holger Rogner, Joyashree Roy, Jayant Sathaye, Robert Schock, Priyaradshi Shukla, Ralph Sims, Pete Smith, Rob Swart, Dennis Tirpak, Diana Urge-Vorsatz, Zhou Dadi
This Summary for Policymakers should be cited as: IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Summary for Policymakers
Table of Contents A.
Introduction ........................................................................................................................................................................... 3
B.
Greenhouse gas emission trends ........................................................................................................................................ 3
C. Mitigation in the short and medium term (until 2030) ................................................................................................ 9 D.
Mitigation in the long term (after 2030) ........................................................................................................................ 15
E. Policies, measures and instruments to mitigate climate change .............................................................................. 19 F.
Sustainable development and climate change mitigation .......................................................................................... 21
G. Gaps in knowledge ............................................................................................................................................................... 22 Endbox 1: Uncertainty representation ................................................................................................................................... 23
2
Summary for Policymakers
A. 1.
Introduction
The Working Group III contribution to the IPCC Fourth Assessment Report (AR4) focuses on new literature on the scientific, technological, environmental, economic and social aspects of mitigation of climate change, published since the IPCC Third Assessment Report (TAR) and the Special Reports on CO2 Capture and Storage (SRCCS) and on Safeguarding the Ozone Layer and the Global Climate System (SROC). The following summary is organised into six sections after this introduction: • Greenhouse gas (GHG) emission trends • Mitigation in the short and medium term, across different economic sectors (until 2030) • Mitigation in the long-term (beyond 2030) • Policies, measures and instruments to mitigate climate change • Sustainable development and climate change mitigation • Gaps in knowledge.
•
•
References to the corresponding chapter sections are indicated at each paragraph in square brackets. An explanation of terms, acronyms and chemical symbols used in this SPM can be found in the glossary to the main report.
B.
Greenhouse gas emission trends
2. Global greenhouse gas (GHG) emissions have grown since pre-industrial times, with an increase of 70% between 1970 and 2004 (high agreement, much evidence)1. • Since pre-industrial times, increasing emissions of GHGs due to human activities have led to a marked increase in atmospheric GHG concentrations [1.3; Working Group I SPM]. • Between 1970 and 2004, global emissions of CO2, CH4, N2O, HFCs, PFCs and SF6, weighted by their global warming potential (GWP), have increased by 70% (24%
1 2
3 4
5 6 7 8
•
•
between 1990 and 2004), from 28.7 to 49 Gigatonnes of carbon dioxide equivalents (GtCO2-eq)2 (see Figure SPM.1). The emissions of these gases have increased at different rates. CO2 emissions have grown between 1970 and 2004 by about 80% (28% between 1990 and 2004) and represented 77% of total anthropogenic GHG emissions in 2004. The largest growth in global GHG emissions between 1970 and 2004 has come from the energy supply sector (an increase of 145%). The growth in direct emissions3 from transport in this period was 120%, industry 65% and land use, land use change, and forestry (LULUCF)4 40%5. Between 1970 and 1990 direct emissions from agriculture grew by 27% and from buildings by 26%, and the latter remained at approximately at 1990 levels thereafter. However, the buildings sector has a high level of electricity use and hence the total of direct and indirect emissions in this sector is much higher (75%) than direct emissions [1.3, 6.1, 11.3, Figures 1.1 and 1.3]. The effect on global emissions of the decrease in global energy intensity (-33%) during 1970 to 2004 has been smaller than the combined effect of global per capita income growth (77 %) and global population growth (69%); both drivers of increasing energy-related CO2 emissions (Figure SPM.2). The long-term trend of a declining carbon intensity of energy supply reversed after 2000. Differences in terms of per capita income, per capita emissions, and energy intensity among countries remain significant. (Figure SPM.3). In 2004 UNFCCC Annex I countries held a 20% share in world population, produced 57% of world Gross Domestic Product based on Purchasing Power Parity (GDPppp)6, and accounted for 46% of global GHG emissions (Figure SPM.3) [1.3]. The emissions of ozone depleting substances (ODS) controlled under the Montreal Protocol7, which are also GHGs, have declined significantly since the 1990s. By 2004 the emissions of these gases were about 20% of their 1990 level [1.3]. A range of policies, including those on climate change, energy security8, and sustainable development, have been effective in reducing GHG emissions in different sectors and many countries. The scale of such measures, however, has not yet been large enough to counteract the global growth in emissions [1.3, 12.2].
Each headline statement has an “agreement/evidence” assessment attached that is supported by the bullets underneath. This does not necessarily mean that this level of “agreement/evidence”applies to each bullet. Endbox 1 provides an explanation of this representation of uncertainty. The definition of carbon dioxide equivalent (CO2-eq) is the amount of CO2 emission that would cause the same radiative forcing as an emitted amount of a well mixed greenhouse gas or a mixture of well mixed greenhouse gases, all multiplied with their respective GWPs to take into account the differing times they remain in the atmosphere [WGI AR4 Glossary]. Direct emissions in each sector do not include emissions from the electricity sector for the electricity consumed in the building, industry and agricultural sectors or of the emissions from refinery operations supplying fuel to the transport sector. The term “land use, land use change and forestry” is used here to describe the aggregated emissions of CO2, CH4, N2O from deforestation, biomass and burning, decay of biomass from logging and deforestation, decay of peat and peat fires [1.3.1]. This is broader than emissions from deforestation, which is included as a subset. The emissions reported here do not include carbon uptake (removals). This trend is for the total LULUCF emissions, of which emissions from deforestation are a subset and, owing to large data uncertainties, is significantly less certain than for other sectors. The rate of deforestation globally was slightly lower in the 2000-2005 period than in the 1990-2000 period [9.2.1]. The GDPppp metric is used for illustrative purposes only for this report. For an explanation of PPP and Market Exchange Rate (MER) GDP calculations, see footnote 12. Halons, chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), methyl chloroform (CH3CCl3), carbon tetrachloride (CCl4) and methyl bromide (CH3Br). Energy security refers to security of energy supply.
3
Summary for Policymakers
Gt CO2eq/yr
5
HFCs, PFCs, SF6
0 5
N2O other1) N2O agriculture
0 10
CH4 other2) CH4 waste
5
CH4 agriculture CH4 energy3)
0 10 5
CO2 decay and peat4)
0
CO2 deforestation5) 6)
30
Figure SPM.1: Global Warming Potential (GWP) weighted global greenhouse gas emissions 1970-2004. 100 year GWPs from IPCC 1996 (SAR) were used to convert emissions to CO2-eq. (cf. UNFCCC reporting guidelines). CO2, CH4, N2O, HFCs, PFCs and SF6 from all sources are included. The two CO2 emission categories reflect CO2 emissions from energy production and use (second from bottom) and from land use changes (third from the bottom) [Figure 1.1a].
Notes: 1. Other N2O includes industrial processes, deforestation/savannah burning, waste water and waste incineration. 2. Other is CH4 from industrial processes and savannah burning. 3. Including emissions from bioenergy production and use 4. CO2 emissions from decay (decomposition) of above ground biomass that remains after logging and deforestation and CO2 from peat fires and decay of drained peat soils. 5. As well as traditional biomass use at 10% of total, assuming 90% is from sustainable biomass production. Corrected for 10% carbon of biomass that is assumed to remain as charcoal after combustion. 6. For large-scale forest and scrubland biomass burning averaged data for 1997-2002 based on Global Fire Emissions Data base satellite data. 7. Cement production and natural gas flaring. 8. Fossil fuel use includes emissions from feedstocks.
CO2 other7)
25 20 15
CO2 fossil fuel use8)
10 5 0 1970
1980
1990 2000 2004
50 40 30
Total GHG
20 10 0 1970
9
4
1980
1990
2000 2004
3. With current climate change mitigation policies and related sustainable development practices, global GHG emissions will continue to grow over the next few decades (high agreement, much evidence). • The SRES (non-mitigation) scenarios project an increase of baseline global GHG emissions by a range of 9.7 GtCO2-eq to 36.7 GtCO2-eq (25-90%) between 2000 and 20309 (Box SPM.1 and Figure SPM.4). In these scenarios, fossil fuels are projected to maintain their dominant position in the global energy mix to 2030 and beyond. Hence CO2 emissions between 2000 and 2030 from energy use are projected to grow 40 to 110% over that period. Two thirds to three quarters of this increase in energy CO2 emissions is projected to come from nonAnnex I regions, with their average per capita energy CO2 emissions being projected to remain substantially lower (2.8-5.1 tCO2/cap) than those in Annex I regions (9.6-15.1 tCO2/cap) by 2030. According to SRES scenarios, their economies are projected to have a lower energy use per unit of GDP (6.2 – 9.9 MJ/US$ GDP) than that of non-Annex I countries (11.0 – 21.6 MJ/US$ GDP). [1.3, 3.2]
The SRES 2000 GHG emissions assumed here are 39.8 GtCO2-eq, i.e. lower than the emissions reported in the EDGAR database for 2000 (45 GtCO2-eq). This is mostly due to differences in LULUCF emissions.
Summary for Policymakers
Index 1970 = 1 3,0
Income (GDP-ppp)
2,8 2,6 2,4 2,2
Energy (TPES)
2,0
1,6
CO2 emissions Income per capita (GDP-ppp/cap)
1,4
Population
1,8
1,2 Carbon intensity (CO2/TPES) Energy intensity (TPES/GDP-ppp)
1,0 0,8 0,6
Emission intensity (CO2/GDP-ppp)
0,4 1970
1975
1980
1985
1990
1995
2000
Figure SPM.2: Relative global development of Gross Domestic Product measured in PPP (GDPppp), Total Primary Energy Supply (TPES), CO2 emissions (from fossil fuel burning, gas flaring and cement manufacturing) and Population (Pop). In addition, in dotted lines, the figure shows Income per capita (GDPppp/Pop), Energy Intensity (TPES/GDPppp), Carbon Intensity of energy supply (CO2/TPES), and Emission Intensity of the economic production process (CO2/GDPppp) for the period 1970-2004. [Figure 1.5]
3.0 Non-Annex I: Population 80.3%
2.5
25
Annex I non-Annex I
2.0
20
0 0
1,000
Middle East: 3.8%
5
Other non-Annex I: 2.0% Europe Annex II: and M & T 11,4%
10
JANZ: 5.2%
USA & Canada: 19,4%
15
EIT Annex I: 9.7%
Average Annex I: 16,1 t CO2eq/cap
Latin America & Carribean: 10.3%
Non-Annex I East Asia: 17,3%
Africa: 7.8%
South Asia:13,1%
2,000 3,000 4,000 5,000 Cumulative population in million
6,000
0.5
Non-Annex I East Asia: 17,3%
0 7,000
Figure SPM.3a: Year 2004 distribution of regional per capita GHG emissions (all Kyoto gases, including those from land-use) over the population of different country groupings. The percentages in the bars indicate a regions share in global GHG emissions [Figure 1.4a].
GHG/GDP kg CO2eq/US$ 0.683 1.055
1.5 1.0
Average non-Annex I: 4,2 t CO2eq/cap
Share in global GDP 56.6% 43.4%
Other non-Annex I: 2.0%
Middle East: 3.8% Latin America & Carribean: 10.3%
Annex I: Population 19.7%
kg CO2eq/US$ GDPppp (2000)
Africa: 7.8%
30
t CO2eq/cap
EIT Annex I: 9.7%
35
0
10,000
South Asia: 13,1%
USA & Canada: 19,4%
JANZ: 5.2%
Europe Annex II and M & T: 11,4%
20,000 30,000 40,000 50,000 Cumulative GDPppp (2000) in billion US$
60,000
Figure SPM.3b: Year 2004 distribution of regional GHG emissions (all Kyoto gases, including those from land-use) per US$ of GDPppp over the GDPppp of different country groupings. The percentages in the bars indicate a regions share in global GHG emissions [Figure 1.4b].
5
Summary for Policymakers
180
Gt CO2-eq/yr F-gases
160
N2O
140 120
CH4
100
CO2
80 60 40
SRES 2030
post SRES
2100
5th
25th
median
95th
SRES
75th
B1
A1T
A1B
B2
A1FI
A2
5th
25th
median
75th
B2
95th
B1
A1T
A2
A1B
A1FI
0
2000
20
post SRES
Figure SPM.4: Global GHG emissions for 2000 and projected baseline emissions10 for 2030 and 2100 from IPCC SRES and the post-SRES literature. The figure provides the emissions from the six illustrative SRES scenarios. It also provides the frequency distribution of the emissions in the post-SRES scenarios (5th, 25th, median, 75th, 95th percentile), as covered in Chapter 3. F-gases cover HFCs, PFCs and SF6 [1.3, 3.2, Figure 1.7].
4. Baseline emissions scenarios published since SRES10, are comparable in range to those presented in the IPCC Special Report on Emission Scenarios (SRES) (25- 135 GtCO2-eq/yr in 2100, see Figure SPM.4) (high agreement, much evidence). • Studies since SRES used lower values for some drivers for emissions, notably population projections. However, for those studies incorporating these new population projections, changes in other drivers, such as economic growth, resulted in little change in overall emission levels. Economic growth projections for Africa, Latin America and the Middle East to 2030 in post-SRES baseline scenarios are lower than in SRES, but this has only minor effects on global economic growth and overall emissions [3.2].
• Representation of aerosol and aerosol precursor emissions, including sulphur dioxide, black carbon, and organic carbon, which have a net cooling effect11 has improved. Generally, they are projected to be lower than reported in SRES [3.2]. • Available studies indicate that the choice of exchange rate for GDP (MER or PPP) does not appreciably affect the projected emissions, when used consistently12. The differences, if any, are small compared to the uncertainties caused by assumptions on other parameters in the scenarios, e.g. technological change [3.2].
10 Baseline scenarios do not include additional climate policy above current ones; more recent studies differ with respect to UNFCCC and Kyoto Protocol inclusion. 11 See AR4 WG I report, Chapter 10.2. 12 Since TAR, there has been a debate on the use of different exchange rates in emission scenarios. Two metrics are used to compare GDP between countries. Use of MER is preferable for analyses involving internationally traded products. Use of PPP, is preferable for analyses involving comparisons of income between countries at very different stages of development. Most of the monetary units in this report are expressed in MER. This reflects the large majority of emissions mitigation literature that is calibrated in MER. When monetary units are expressed in PPP, this is denoted by GDPppp.
6
Summary for Policymakers
Box SPM.1: The emission scenarios of the IPCC Special Report on Emission Scenarios (SRES) A1. The A1 storyline and scenario family describes a future world of very rapid economic growth, global population that peaks in mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building and increased cultural and social interactions, with a substantial reduction in regional differences in per capita income. The A1 scenario family develops into three groups that describe alternative directions of technological change in the energy system. The three A1 groups are distinguished by their technological emphasis: fossil intensive (A1FI), non fossil energy sources (A1T), or a balance across all sources (A1B) (where balanced is defined as not relying too heavily on one particular energy source, on the assumption that similar improvement rates apply to all energy supply and end use technologies). A2. The A2 storyline and scenario family describes a very heterogeneous world. The underlying theme is self reliance and preservation of local identities. Fertility patterns across regions converge very slowly, which results in continuously increasing population. Economic development is primarily regionally oriented and per capita economic growth and technological change more fragmented and slower than other storylines. B1. The B1 storyline and scenario family describes a convergent world with the same global population, that peaks in midcentury and declines thereafter, as in the A1 storyline, but with rapid change in economic structures toward a service and information economy, with reductions in material intensity and the introduction of clean and resource efficient technologies. The emphasis is on global solutions to economic, social and environmental sustainability, including improved equity, but without additional climate initiatives. B2. The B2 storyline and scenario family describes a world in which the emphasis is on local solutions to economic, social and environmental sustainability. It is a world with continuously increasing global population, at a rate lower than A2, intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 storylines. While the scenario is also oriented towards environmental protection and social equity, it focuses on local and regional levels. An illustrative scenario was chosen for each of the six scenario groups A1B, A1FI, A1T, A2, B1 and B2. All should be considered equally sound. The SRES scenarios do not include additional climate initiatives, which means that no scenarios are included that explicitly assume implementation of the United Nations Framework Convention on Climate Change or the emissions targets of the Kyoto Protocol. This box summarizing the SRES scenarios is taken from the Third Assessment Report and has been subject to prior line by line approval by the Panel.
Box SPM.2: Mitigation potential and analytical approaches The concept of “mitigation potential” has been developed to assess the scale of GHG reductions that could be made, relative to emission baselines, for a given level of carbon price (expressed in cost per unit of carbon dioxide equivalent emissions avoided or reduced). Mitigation potential is further differentiated in terms of “market potential” and “economic potential”. Market potential is the mitigation potential based on private costs and private discount rates13, which might be expected to occur under forecast market conditions, including policies and measures currently in place, noting that barriers limit actual uptake [2.4].
13 Private costs and discount rates reflect the perspective of private consumers and companies; see Glossary for a fuller description.
7
Summary for Policymakers
(Box SPM.2 Continued) Economic potential is the mitigation potential, which takes into account social costs and benefits and social discount rates14, assuming that market efficiency is improved by policies and measures and barriers are removed [2.4]. Studies of market potential can be used to inform policy makers about mitigation potential with existing policies and barriers, while studies of economic potentials show what might be achieved if appropriate new and additional policies were put into place to remove barriers and include social costs and benefits. The economic potential is therefore generally greater than the market potential. Mitigation potential is estimated using different types of approaches. There are two broad classes – “bottom-up” and “topdown” approaches, which primarily have been used to assess the economic potential. Bottom-up studies are based on assessment of mitigation options, emphasizing specific technologies and regulations. They are typically sectoral studies taking the macro-economy as unchanged. Sector estimates have been aggregated, as in the TAR, to provide an estimate of global mitigation potential for this assessment. Top-down studies assess the economy-wide potential of mitigation options. They use globally consistent frameworks and aggregated information about mitigation options and capture macro-economic and market feedbacks. Bottom-up and top-down models have become more similar since the TAR as top-down models have incorporated more technological mitigation options and bottom-up models have incorporated more macroeconomic and market feedbacks as well as adopting barrier analysis into their model structures. Bottom-up studies in particular are useful for the assessment of specific policy options at sectoral level, e.g. options for improving energy efficiency, while top-down studies are useful for assessing cross-sectoral and economy-wide climate change policies, such as carbon taxes and stabilization policies. However, current bottom-up and top-down studies of economic potential have limitations in considering life-style choices, and in including all externalities such as local air pollution. They have limited representation of some regions, countries, sectors, gases, and barriers. The projected mitigation costs do not take into account potential benefits of avoided climate change.
Box SPM.3: Assumptions in studies on mitigation portfolios and macro-economic costs Studies on mitigation portfolios and macro-economic costs assessed in this report are based on top-down modelling. Most models use a global least cost approach to mitigation portfolios and with universal emissions trading, assuming transparent markets, no transaction cost, and thus perfect implementation of mitigation measures throughout the 21st century. Costs are given for a specific point in time. Global modelled costs will increase if some regions, sectors (e.g. land-use), options or gases are excluded. Global modelled costs will decrease with lower baselines, use of revenues from carbon taxes and auctioned permits, and if induced technological learning is included. These models do not consider climate benefits and generally also co-benefits of mitigation measures, or equity issues.
Box SPM.4: Modelling induced technological change Relevant literature implies that policies and measures may induce technological change. Remarkable progress has been achieved in applying approaches based on induced technological change to stabilisation studies; however, conceptual issues remain. In the models that adopt these approaches, projected costs for a given stabilization level are reduced; the reductions are greater at lower stabilisation levels.
14 Social costs and discount rates reflect the perspective of society. Social discount rates are lower than those used by private investors; see Glossary for a fuller description.
8
Summary for Policymakers
C.
• Studies suggest that mitigation opportunities with net negative costs15 have the potential to reduce emissions by around 6 GtCO2-eq/yr in 2030. Realizing these requires dealing with implementation barriers [11.3]. • No one sector or technology can address the entire mitigation challenge. All assessed sectors contribute to the total (see Figure SPM.6). The key mitigation technologies and practices for the respective sectors are shown in Table SPM 3 [4.3, 4.4, 5.4, 6.5, 7.5, 8.4, 9.4, 10.4].
Mitigation in the short and medium term (until 2030)
5. Both bottom-up and top-down studies indicate that there is substantial economic potential for the mitigation of global GHG emissions over the coming decades, that could offset the projected growth of global emissions or reduce emissions below current levels (high agreement, much evidence). Uncertainties in the estimates are shown as ranges in the tables below to reflect the ranges of baselines, rates of technological change and other factors that are specific to the different approaches. Furthermore, uncertainties also arise from the limited information for global coverage of countries, sectors and gases.
Top-down studies: • Top-down studies calculate an emission reduction for 2030 as presented in Table SPM.2 below and Figure SPM.5B. The global economic potentials found in the top-down studies are in line with bottom-up studies (see Box SPM.2), though there are considerable differences at the sectoral level [3.6]. • The estimates in Table SPM.2 were derived from stabilization scenarios, i.e., runs towards long-run stabilization of atmospheric GHG concentration [3.6].
Bottom-up studies: • In 2030, the economic potential estimated for this assessment from bottom-up approaches (see Box SPM.2) is presented in Table SPM.1 below and Figure SPM.5A. For reference: emissions in 2000 were equal to 43 GtCO2-eq. [11.3]:
Table SPM.1: Global economic mitigation potential in 2030 estimated from bottom-up studies. Carbon price (US$/tCO2-eq)
Economic potential (GtCO2-eq/yr)
Reduction relative to SRES A1 B (68 GtCO2-eq/yr) (%)
Reduction relative to SRES B2 (49 GtCO2-eq/yr) (%)
0
5-7
7-10
10-14
20
9-17
14-25
19-35
50
13-26
20-38
27-52
100
16-31
23-46
32-63
Economic potential (GtCO2-eq/yr)
Reduction relative to SRES A1 B (68 GtCO2-eq/yr) (%)
Reduction relative to SRES B2 (49 GtCO2-eq/yr) (%)
20
9-18
13-27
18-37
50
14-23
21-34
29-47
100
17-26
25-38
35-53
Table SPM.2: Global economic mitigation potential in 2030 estimated from top-down studies. Carbon price (US$/tCO2-eq)
15 In this report, as in the SAR and the TAR, options with net negative costs (no regrets opportunities) are defined as those options whose benefits such as reduced energy costs and reduced emissions of local/regional pollutants equal or exceed their costs to society, excluding the benefits of avoided climate change (see Box SPM.1).
9
Summary for Policymakers
35
GtCO2-eq
35
30
30
25
25
20
20
15
15
10
10
5
5
0
GtCO2-eq
0
low end of range
<0
<20
high end of range
<50
low end of range
<100 US$/tCO2-eq
Figure SPM.5A: Global economic mitigation potential in 2030 estimated from bottom-up studies (data from Table SPM.1)
<20
<50
high end of range
<100 US$/tCO2-eq
Figure SPM.5B: Global economic mitigation potential in 2030 estimated from top-down studies (data from Table SPM.2)
Table SPM.3: Key mitigation technologies and practices by sector. Sectors and technologies are listed in no particular order. Non-technological practices, such as lifestyle changes, which are cross-cutting, are not included in this table (but are addressed in paragraph 7 in this SPM). Sector
Key mitigation technologies and practices currently commercially available
Key mitigation technologies and practices projected to be commercialized before 2030
Energy supply [4.3, 4.4]
Improved supply and distribution efficiency; fuel switching from coal to gas; nuclear power; renewable heat and power (hydropower, solar, wind, geothermal and bioenergy); combined heat and power; early applications of Carbon Capture and Storage (CCS, e.g. storage of removed CO2 from natural gas).
CCS for gas, biomass and coal-fired electricity generating facilities; advanced nuclear power; advanced renewable energy, including tidal and waves energy, concentrating solar, and solar PV.
Transport [5.4]
More fuel efficient vehicles; hybrid vehicles; cleaner diesel Second generation biofuels; higher efficiency aircraft; vehicles; biofuels; modal shifts from road transport to rail and advanced electric and hybrid vehicles with more powerful public transport systems; non-motorised transport (cycling, and reliable batteries. walking); land-use and transport planning.
Buildings [6.5]
Efficient lighting and daylighting; more efficient electrical appliances and heating and cooling devices; improved cook stoves, improved insulation ; passive and active solar design for heating and cooling; alternative refrigeration fluids, recovery and recycle of fluorinated gases.
Integrated design of commercial buildings including technologies, such as intelligent meters that provide feedback and control; solar PV integrated in buildings.
Industry [7.5]
More efficient end-use electrical equipment; heat and power recovery; material recycling and substitution; control of nonCO2 gas emissions; and a wide array of process-specific technologies.
Advanced energy efficiency; CCS for cement, ammonia, and iron manufacture; inert electrodes for aluminium manufacture.
Agriculture [8.4]
Improved crop and grazing land management to increase soil carbon storage; restoration of cultivated peaty soils and degraded lands; improved rice cultivation techniques and livestock and manure management to reduce CH4 emissions; improved nitrogen fertilizer application techniques to reduce N2O emissions; dedicated energy crops to replace fossil fuel use; improved energy efficiency.
Improvements of crops yields.
Forestry/forests [9.4]
Afforestation; reforestation; forest management; reduced deforestation; harvested wood product management; use of forestry products for bioenergy to replace fossil fuel use.
Tree species improvement to increase biomass productivity and carbon sequestration. Improved remote sensing technologies for analysis of vegetation/ soil carbon sequestration potential and mapping land use change.
Waste management [10.4]
Landfill methane recovery; waste incineration with energy recovery; composting of organic waste; controlled waste water treatment; recycling and waste minimization.
Biocovers and biofilters to optimize CH4 oxidation.
10
Summary for Policymakers
7
GtCO2-eq/yr
6 5 4 3 2
Non-OECD/EIT EIT OECD World total
1
Energy supply (potential at
Transport
Buildings
Industry
Agriculture
Forestry
(potential at
(potential at
(potential at
(potential at
(potential at
0 <1 0
0
<5 0
<2
0
0 <1 0
<5
<2 0
0
<5 0 <1 00
<2
00
<5 0
<1
0 <2
00
0 <5
<1
0 <2
00
0 <5
<1
0 <2
0
00 <1
<5
<2
0
0
US$/tCO2-eq
Waste (potential at
Figure SPM.6: Estimated sectoral economic potential for global mitigation for different regions as a function of carbon price in 2030 from bottom-up studies, compared to the respective baselines assumed in the sector assessments. A full explanation of the derivation of this figure is found in Section 11.3. Notes: 1. The ranges for global economic potentials as assessed in each sector are shown by vertical lines. The ranges are based on end-use allocations of emissions, meaning that emissions of electricity use are counted towards the end-use sectors and not to the energy supply sector. 2. The estimated potentials have been constrained by the availability of studies particularly at high carbon price levels. 3. Sectors used different baselines. For industry the SRES B2 baseline was taken, for energy supply and transport the WEO 2004 baseline was used; the building sector is based on a baseline in between SRES B2 and A1B; for waste, SRES A1B driving forces were used to construct a waste specific baseline, agriculture and forestry used baselines that mostly used B2 driving forces. 4. Only global totals for transport are shown because international aviation is included [5.4]. 5. Categories excluded are: non-CO2 emissions in buildings and transport, part of material efficiency options, heat production and cogeneration in energy supply, heavy duty vehicles, shipping and high-occupancy passenger transport, most high-cost options for buildings, wastewater treatment, emission reduction from coal mines and gas pipelines, fluorinated gases from energy supply and transport. The underestimation of the total economic potential from these emissions is of the order of 10-15%.
6. In 2030 macro-economic costs for multi-gas mitigation, consistent with emissions trajectories towards stabilization between 445 and 710 ppm CO2-eq, are estimated at between a 3% decrease of global GDP and a small increase, compared to the baseline (see Table SPM.4). However, regional costs may differ significantly from global averages (high agreement, medium evidence) (see Box SPM.3 for the methodologies and assumptions of these results). • The majority of studies conclude that reduction of GDP relative to the GDP baseline increases with the stringency of the stabilization target. • Depending on the existing tax system and spending of the revenues, modelling studies indicate that costs may be substantially lower under the assumption that revenues from carbon taxes or auctioned permits under an emission trading system are used to promote lowcarbon technologies or reform of existing taxes [11.4].
• Studies that assume the possibility that climate change policy induces enhanced technological change also give lower costs. However, this may require higher upfront investment in order to achieve costs reductions thereafter (see Box SPM.4) [3.3, 3.4, 11.4, 11.5, 11.6]. • Although most models show GDP losses, some show GDP gains because they assume that baselines are non-optimal and mitigation policies improve market efficiencies, or they assume that more technological change may be induced by mitigation policies. Examples of market inefficiencies include unemployed resources, distortionary taxes and/or subsidies [3.3, 11.4]. • A multi-gas approach and inclusion of carbon sinks generally reduces costs substantially compared to CO2 emission abatement only [3.3]. • Regional costs are largely dependent on the assumed stabilization level and baseline scenario. The allocation regime is also important, but for most countries to a lesser extent than the stabilization level [11.4, 13.3]. 11
Summary for Policymakers
Table SPM.4: Estimated global macro-economic costs in 2030a) for least-cost trajectories towards different long-term stabilization levels.b), c) Stabilization levels (ppm CO2-eq)
Median GDP reductiond) (%)
Range of GDP reductiond), e) (%)
Reduction of average annual GDP growth ratesd), f) (percentage points)
590-710
0.2
-0.6-1.2
<0.06
535-590
0.6
0.2-2.5
<0.1
445-535g)
not available
<3
<0.12
Notes: a) For a given stabilization level, GDP reduction would increase over time in most models after 2030. Long-term costs also become more uncertain. [Figure 3.25] b) Results based on studies using various baselines. c) Studies vary in terms of the point in time stabilization is achieved; generally this is in 2100 or later. d) This is global GDP based market exchange rates. e) The median and the 10th and 90th percentile range of the analyzed data are given. f) The calculation of the reduction of the annual growth rate is based on the average reduction during the period till 2030 that would result in the indicated GDP decrease in 2030. g) The number of studies that report GDP results is relatively small and they generally use low baselines.
• Including co-benefits other than health, such as increased energy security, and increased agricultural production and reduced pressure on natural ecosystems, due to decreased tropospheric ozone concentrations, would further enhance cost savings [11.8]. • Integrating air pollution abatement and climate change mitigation policies offers potentially large cost reductions compared to treating those policies in isolation [11.8].
7. Changes in lifestyle and behaviour patterns can contribute to climate change mitigation across all sectors. Management practices can also have a positive role (high agreement, medium evidence). • Lifestyle changes can reduce GHG emissions. Changes in lifestyles and consumption patterns that emphasize resource conservation can contribute to developing a low-carbon economy that is both equitable and sustainable [4.1, 6.7]. • Education and training programmes can help overcome barriers to the market acceptance of energy efficiency, particularly in combination with other measures [Table 6.6]. • Changes in occupant behaviour, cultural patterns and consumer choice and use of technologies can result in considerable reduction in CO2 emissions related to energy use in buildings [6.7]. • Transport Demand Management, which includes urban planning (that can reduce the demand for travel) and provision of information and educational techniques (that can reduce car usage and lead to an efficient driving style) can support GHG mitigation [5.1]. • In industry, management tools that include staff training, reward systems, regular feedback, documentation of existing practices can help overcome industrial organization barriers, reduce energy use, and GHG emissions [7.3].
9. Literature since TAR confirms that there may be effects from Annex I countries’ action on the global economy and global emissions, although the scale of carbon leakage remains uncertain (high agreement, medium evidence). • Fossil fuel exporting nations (in both Annex I and nonAnnex I countries) may expect, as indicated in TAR16, lower demand and prices and lower GDP growth due to mitigation policies. The extent of this spill over17 depends strongly on assumptions related to policy decisions and oil market conditions [11.7]. • Critical uncertainties remain in the assessment of carbon leakage18. Most equilibrium modelling support the conclusion in the TAR of economy-wide leakage from Kyoto action in the order of 5-20%, which would be less if competitive low-emissions technologies were effectively diffused [11.7] .
8. While studies use different methodologies, in all analyzed world regions near-term health co-benefits from reduced air pollution as a result of actions to reduce GHG emissions can be substantial and may offset a substantial fraction of mitigation costs (high agreement, much evidence).
10. New energy infrastructure investments in developing countries, upgrades of energy infrastructure in industrialized countries, and policies that promote energy security, can, in many cases, create opportunities to achieve GHG emission reductions19 compared to baseline scenarios. Additional co-benefits are country-
16 See TAR WG III (2001) SPM paragraph 16. 17 Spill over effects of mitigation in a cross-sectoral perspective are the effects of mitigation policies and measures in one country or group of countries on sectors in other countries. 18 Carbon leakage is defined as the increase in CO2 emissions outside the countries taking domestic mitigation action divided by the reduction in the emissions of these countries. 19 See table SPM.3 and Figure SPM.6
12
Summary for Policymakers
specific but often include air pollution abatement, balance of trade improvement, provision of modern energy services to rural areas and employment (high agreement, much evidence). • Future energy infrastructure investment decisions, expected to total over 20 trillion US$20 between now and 2030, will have long term impacts on GHG emissions, because of the long life-times of energy plants and other infrastructure capital stock. The widespread diffusion of low-carbon technologies may take many decades, even if early investments in these technologies are made attractive. Initial estimates show that returning global energy-related CO2 emissions to 2005 levels by 2030 would require a large shift in the pattern of investment, although the net additional investment required ranges from negligible to 5-10% [4.1, 4.4, 11.6]. • It is often more cost-effective to invest in end-use energy efficiency improvement than in increasing energy supply to satisfy demand for energy services. Efficiency improvement has a positive effect on energy security, local and regional air pollution abatement, and employment [4.2, 4.3, 6.5, 7.7, 11.3, 11.8]. • Renewable energy generally has a positive effect on energy security, employment and on air quality. Given costs relative to other supply options, renewable electricity, which accounted for 18% of the electricity supply in 2005, can have a 30-35% share of the total electricity supply in 2030 at carbon prices up to 50 US$/tCO2-eq [4.3, 4.4, 11.3, 11.6, 11.8]. • The higher the market prices of fossil fuels, the more low-carbon alternatives will be competitive, although price volatility will be a disincentive for investors. Higher priced conventional oil resources, on the other hand, may be replaced by high carbon alternatives such as from oil sands, oil shales, heavy oils, and synthetic fuels from coal and gas, leading to increasing GHG emissions, unless production plants are equipped with CCS [4.2, 4.3, 4.4, 4.5]. • Given costs relative to other supply options, nuclear power, which accounted for 16% of the electricity supply in 2005, can have an 18% share of the total electricity supply in 2030 at carbon prices up to 50 US$/tCO2-eq, but safety, weapons proliferation and waste remain as constraints [4.2, 4.3, 4.4]21. • CCS in underground geological formations is a new technology with the potential to make an important contribution to mitigation by 2030. Technical, economic and regulatory developments will affect the actual contribution [4.3, 4.4, 7.3].
11. There are multiple mitigation options in the transport sector19, but their effect may be counteracted by growth in the sector. Mitigation options are faced with many barriers, such as consumer preferences and lack of policy frameworks (medium agreement, medium evidence). • Improved vehicle efficiency measures, leading to fuel savings, in many cases have net benefits (at least for light-duty vehicles), but the market potential is much lower than the economic potential due to the influence of other consumer considerations, such as performance and size. There is not enough information to assess the mitigation potential for heavy-duty vehicles. Market forces alone, including rising fuel costs, are therefore not expected to lead to significant emission reductions [5.3, 5.4]. • Biofuels might play an important role in addressing GHG emissions in the transport sector, depending on their production pathway. Biofuels used as gasoline and diesel fuel additives/substitutes are projected to grow to 3% of total transport energy demand in the baseline in 2030. This could increase to about 5-10%, depending on future oil and carbon prices, improvements in vehicle efficiency and the success of technologies to utilise cellulose biomass [5.3, 5.4]. • Modal shifts from road to rail and to inland and coastal shipping and from low-occupancy to highoccupancy passenger transportation22, as well as landuse, urban planning and non-motorized transport offer opportunities for GHG mitigation, depending on local conditions and policies [5.3, 5.5]. • Medium term mitigation potential for CO2 emissions from the aviation sector can come from improved fuel efficiency, which can be achieved through a variety of means, including technology, operations and air traffic management. However, such improvements are expected to only partially offset the growth of aviation emissions. Total mitigation potential in the sector would also need to account for non-CO2 climate impacts of aviation emissions [5.3, 5.4]. • Realizing emissions reductions in the transport sector is often a co-benefit of addressing traffic congestion, air quality and energy security [5.5]. 12. Energy efficiency options19 for new and existing buildings could considerably reduce CO2 emissions with net economic benefit. Many barriers exist against tapping this potential, but there are also large co-benefits (high agreement, much evidence). • By 2030, about 30% of the projected GHG emissions in the building sector can be avoided with net economic benefit [6.4, 6.5].
20 20 trillion = 20000 billion= 20*1012. 21 Austria could not agree with this statement. 22 Including rail, road and marine mass transit and carpooling.
13
Summary for Policymakers
• Energy efficient buildings, while limiting the growth of CO2 emissions, can also improve indoor and outdoor air quality, improve social welfare and enhance energy security [6.6, 6.7]. • Opportunities for realising GHG reductions in the building sector exist worldwide. However, multiple barriers make it difficult to realise this potential. These barriers include availability of technology, financing, poverty, higher costs of reliable information, limitations inherent in building designs and an appropriate portfolio of policies and programs [6.7, 6.8]. • The magnitude of the above barriers is higher in the developing countries and this makes it more difficult for them to achieve the GHG reduction potential of the building sector [6.7]. 13. The economic potential in the industrial sector19 is predominantly located in energy intensive industries. Full use of available mitigation options is not being made in either industrialized or developing nations (high agreement, much evidence). • Many industrial facilities in developing countries are new and include the latest technology with the lowest specific emissions. However, many older, inefficient facilities remain in both industrialized and developing countries. Upgrading these facilities can deliver significant emission reductions [7.1, 7.3, 7.4]. • The slow rate of capital stock turnover, lack of financial and technical resources, and limitations in the ability of firms, particularly small and medium-sized enterprises, to access and absorb technological information are key barriers to full use of available mitigation options [7.6]. 14. Agricultural practices collectively can make a significant contribution at low cost19 to increasing soil carbon sinks, to GHG emission reductions, and by contributing biomass feedstocks for energy use (medium agreement, medium evidence). • A large proportion of the mitigation potential of agriculture (excluding bioenergy) arises from soil carbon sequestration, which has strong synergies with sustainable agriculture and generally reduces vulnerability to climate change [8.4, 8.5, 8.8]. • Stored soil carbon may be vulnerable to loss through both land management change and climate change [8.10]. • Considerable mitigation potential is also available from reductions in methane and nitrous oxide emissions in some agricultural systems [8.4, 8.5].
• There is no universally applicable list of mitigation practices; practices need to be evaluated for individual agricultural systems and settings [8.4]. • Biomass from agricultural residues and dedicated energy crops can be an important bioenergy feedstock, but its contribution to mitigation depends on demand for bioenergy from transport and energy supply, on water availability, and on requirements of land for food and fibre production. Widespread use of agricultural land for biomass production for energy may compete with other land uses and can have positive and negative environmental impacts and implications for food security [8.4, 8.8]. 15. Forest-related mitigation activities can considerably reduce emissions from sources and increase CO2 removals by sinks at low costs19, and can be designed to create synergies with adaptation and sustainable development (high agreement, much evidence)23. • About 65% of the total mitigation potential (up to 100 US$/tCO2-eq) is located in the tropics and about 50% of the total could be achieved by reducing emissions from deforestation [9.4]. • Climate change can affect the mitigation potential of the forest sector (i.e., native and planted forests) and is expected to be different for different regions and subregions, both in magnitude and direction [9.5]. • Forest-related mitigation options can be designed and implemented to be compatible with adaptation, and can have substantial co-benefits in terms of employment, income generation, biodiversity and watershed conservation, renewable energy supply and poverty alleviation [9.5, 9.6, 9.7]. 16. Post-consumer waste24 is a small contributor to global GHG emissions25 (<5%), but the waste sector can positively contribute to GHG mitigation at low cost19 and promote sustainable development (high agreement, much evidence). • Existing waste management practices can provide effective mitigation of GHG emissions from this sector: a wide range of mature, environmentally effective technologies are commercially available to mitigate emissions and provide co-benefits for improved public health and safety, soil protection and pollution prevention, and local energy supply [10.3, 10.4, 10.5]. • Waste minimization and recycling provide important indirect mitigation benefits through the conservation of energy and materials [10.4].
23 Tuvalu noted difficulties with the reference to “low costs” as Chapter 9, page 15 of the WG III report states that: “the cost of forest mitigation projects rise significantly when opportunity costs of land are taken into account”. 24 Industrial waste is covered in the industry sector. 25 GHGs from waste include landfill and wastewater methane, wastewater N2O, and CO2 from incineration of fossil carbon.
14
Summary for Policymakers
• Lack of local capital is a key constraint for waste and wastewater management in developing countries and countries with economies in transition. Lack of expertise on sustainable technology is also an important barrier [10.6].
• Recent studies using multi-gas reduction have explored lower stabilization levels than reported in TAR [3.3]. • Assessed studies contain a range of emissions profiles for achieving stabilization of GHG concentrations27. Most of these studies used a least cost approach and include both early and delayed emission reductions (Figure SPM.7) [Box SPM.2]. Table SPM.5 summarizes the required emissions levels for different groups of stabilization concentrations and the associated equilibrium global mean temperature increase28, using the ‘best estimate’ of climate sensitivity (see also Figure SPM.8 for the likely range of uncertainty)29. Stabilization at lower concentration and related equilibrium temperature levels advances the date when emissions need to peak, and requires greater emissions reductions by 2050 [3.3].
17. Geo-engineering options, such as ocean fertilization to remove CO2 directly from the atmosphere, or blocking sunlight by bringing material into the upper atmosphere, remain largely speculative and unproven, and with the risk of unknown side-effects. Reliable cost estimates for these options have not been published (medium agreement, limited evidence) [11.2].
D.
Mitigation in the long term (after 2030)
18. In order to stabilize the concentration of GHGs in the atmosphere, emissions would need to peak and decline thereafter. The lower the stabilization level, the more quickly this peak and decline would need to occur. Mitigation efforts over the next two to three decades will have a large impact on opportunities to achieve lower stabilization levels (see Table SPM.5, and Figure SPM. 8)26 (high agreement, much evidence).
Table SPM.5: Characteristics of post-TAR stabilization scenarios [Table TS 2, 3.10]a)
Radiative forcing Category (W/m2)
CO2 concentrationc) (ppm)
CO2-eq concentrationc) (ppm)
Global mean temperature increase above preindustrial at equilibrium, using “best estimate” climate sensitivityb), c) (ºC)
Peaking year for CO2 emissionsd)
Change in global CO2 emissions in 2050 (% of 2000 emissions)d)
No. of assessed scenarios
I
2.5-3.0
350-400
445-490
2.0-2.4
2000-2015
-85 to -50
6
II
3.0-3.5
400-440
490-535
2.4-2.8
2000-2020
-60 to -30
18
III
3.5-4.0
440-485
535-590
2.8-3.2
2010-2030
-30 to +5
21
IV
4.0-5.0
485-570
590-710
3.2-4.0
2020-2060
+10 to +60
118
V
5.0-6.0
570-660
710-855
4.0-4.9
2050-2080
+25 to +85
9
VI
6.0-7.5
660-790
855-1130
4.9-6.1
2060-2090
+90 to +140
5
Total
177
a) The understanding of the climate system response to radiative forcing as well as feedbacks is assessed in detail in the AR4 WGI Report. Feedbacks between the carbon cycle and climate change affect the required mitigation for a particular stabilization level of atmospheric carbon dioxide concentration. These feedbacks are expected to increase the fraction of anthropogenic emissions that remains in the atmosphere as the climate system warms. Therefore, the emission reductions to meet a particular stabilization level reported in the mitigation studies assessed here might be underestimated. b) The best estimate of climate sensitivity is 3ºC [WG 1 SPM]. c) Note that global mean temperature at equilibrium is different from expected global mean temperature at the time of stabilization of GHG concentrations due to the inertia of the climate system. For the majority of scenarios assessed, stabilisation of GHG concentrations occurs between 2100 and 2150. d) Ranges correspond to the 15th to 85th percentile of the post-TAR scenario distribution. CO2 emissions are shown so multi-gas scenarios can be compared with CO2only scenarios.
26 27 28 29
Paragraph 2 addresses historical GHG emissions since pre-industrial times. Studies vary in terms of the point in time stabilization is achieved; generally this is around 2100 or later. The information on global mean temperature is taken from the AR4 WGI report, chapter 10.8. These temperatures are reached well after concentrations are stabilized. The equilibrium climate sensitivity is a measure of the climate system response to sustained radiative forcing. It is not a projection but is defined as the global average surface warming following a doubling of carbon dioxide concentrations [AR4 WGI SPM].
15
Summary for Policymakers
90 75 60
GtCO2/year
Category I
90
350 - 400 ppm CO2 445 - 490 ppm CO2 eq. n = 6 Scenarios peaking year 2000-2015
75 60
45
45
30
30
15
15
0
0
-15
-15
-30 2000
90 75 60
2020
GtCO2/year
2040
2060
2080
2100
90
45
30
30
15
15
0
0
-15
-15
90
GtCO2/year
2040
2060
2080
2100
Category V 650 ppm CO2 TAR Range
75
90 60 45
30
30
15
15 0
570 - 660 ppm CO2 710 - 855 ppm CO2 eq. n = 9 Scenarios peaking year 2050-2080
-30 2000
2020
-15 2040
2080
2100
2060
2080
550 ppm CO2 TAR Range
2100
485 - 570 ppm CO2 590 - 710 ppm CO2 eq. n = 118 Scenarios peaking year 2020-2060
2020
2040
2060
2080
2100
Category VI
GtCO2/year
75
45
-15
2060
Category IV
GtCO2/year
-30 2000
60
0
2040
60
45
2020
2020
75 450 ppm CO2 TAR Range
-30 2000
400 - 440 ppm CO2 490 - 535 ppm CO2 eq. n = 18 Scenarios peaking year 2000-2020
-30 2000
Category III
440 - 485 ppm CO2 535 - 590 ppm CO2 eq. n = 21 Scenarios peaking year 2010-2030
Category II
GtCO2/year
750 ppm CO2 TAR Range 660 - 790 ppm CO2 855 - 1130 ppm CO2 eq. n = 5 Scenarios peaking year 2060-2090
-30 2000
2020
2040
2060
2080
2100
Figure SPM.7: Emissions pathways of mitigation scenarios for alternative categories of stabilization levels (Category I to VI as defined in the box in each panel). The pathways are for CO2 emissions only. Light brown shaded areas give the CO2 emissions for the post-TAR emissions scenarios. Green shaded and hatched areas depict the range of more than 80 TAR stabilization scenarios. Base year emissions may differ between models due to differences in sector and industry coverage. To reach the lower stabilization levels some scenarios deploy removal of CO2 from the atmosphere (negative emissions) using technologies such as biomass energy production utilizing carbon capture and storage. [Figure 3.17]
19. The range of stabilization levels assessed can be achieved by deployment of a portfolio of technologies that are currently available and those that are expected to be commercialised in coming decades. This assumes that appropriate and effective incentives are in place for development, acquisition, deployment and diffusion of technologies and for addressing related barriers (high agreement, much evidence). • The contribution of different technologies to emission reductions required for stabilization will vary over time, region and stabilization level. o Energy efficiency plays a key role across many scenarios for most regions and timescales. 16
o For lower stabilization levels, scenarios put more emphasis on the use of low-carbon energy sources, such as renewable energy and nuclear power, and the use of CO2 capture and storage (CCS). In these scenarios improvements of carbon intensity of energy supply and the whole economy need to be much faster than in the past. o Including non-CO2 and CO2 land-use and forestry mitigation options provides greater flexibility and cost-effectiveness for achieving stabilization. Modern bioenergy could contribute substantially to the share of renewable energy in the mitigation portfolio.
Summary for Policymakers
Equilibrium global mean temperature increase above pre-industrial (°C) 10 8 VI
6
V IV
4 I
II
III
2 0 300
400 500 600 700 800 GHG concentration stabilization level (ppm CO2-eq)
900
1000
Figure SPM.8: Stabilization scenario categories as reported in Figure SPM.7 (coloured bands) and their relationship to equilibrium global mean temperature change above pre-industrial, using (i) “best estimate” climate sensitivity of 3°C (black line in middle of shaded area), (ii) upper bound of likely range of climate sensitivity of 4.5°C (red line at top of shaded area) (iii) lower bound of likely range of climate sensitivity of 2°C (blue line at bottom of shaded area). Coloured shading shows the concentration bands for stabilization of greenhouse gases in the atmosphere corresponding to the stabilization scenario categories I to VI as indicated in Figure SPM.7. The data are drawn from AR4 WGI, Chapter 10.8.
o For illustrative examples of portfolios of mitigation options, see figure SPM.9 [3.3, 3.4]. • Investments in and world-wide deployment of lowGHG emission technologies as well as technology improvements through public and private Research,
Development & Demonstration (RD&D) would be required for achieving stabilization targets as well as cost reduction. The lower the stabilization levels, especially those of 550 ppm CO2-eq or lower, the greater the need for more efficient RD&D efforts and investment in new
2000 - 2030
2000 - 2100
Energy conservation & efficiency emissions reductions for 650 ppm
Fossil fuel switch
additional reductions for 490-540 ppm
Renewables Nuclear CCS IMAGE MESSAGE
Forest sinks
AIM IPAC
Non-CO2 0 20 40 60 80 100 120 Cumulative emission reduction GtCO2-eq
0
120
500
1000 1500 Cumulative emission reduction GtCO2-eq
N/A
2000
Figure SPM.9: Cumulative emissions reductions for alternative mitigation measures for 2000 to 2030 (left-hand panel) and for 2000-2100 (right-hand panel). The figure shows illustrative scenarios from four models (AIM, IMAGE, IPAC and MESSAGE) aiming at the stabilization at 490-540 ppm CO2-eq and levels of 650 ppm CO2-eq, respectively. Dark bars denote reductions for a target of 650 ppm CO2-eq and light bars the additional reductions to achieve 490-540 ppm CO2-eq. Note that some models do not consider mitigation through forest sink enhancement (AIM and IPAC) or CCS (AIM) and that the share of low-carbon energy options in total energy supply is also determined by inclusion of these options in the baseline. CCS includes carbon capture and storage from biomass. Forest sinks include reducing emissions from deforestation. [Figure 3.23]
17
Summary for Policymakers
technologies during the next few decades. This requires that barriers to development, acquisition, deployment and diffusion of technologies are effectively addressed. • Appropriate incentives could address these barriers and help realize the goals across a wide portfolio of technologies. [2.7, 3.3, 3.4, 3.6, 4.3, 4.4, 4.6].
• Integrated assessment of the economic costs and benefits of different mitigation pathways shows that the economically optimal timing and level of mitigation depends upon the uncertain shape and character of the assumed climate change damage cost curve. To illustrate this dependency:
20. In 205030 global average macro-economic costs for multi-gas mitigation towards stabilization between 710 and 445 ppm CO2-eq, are between a 1% gain to a 5.5% decrease of global GDP (see Table SPM.6). For specific countries and sectors, costs vary considerably from the global average. (See Box SPM.3 and SPM.4 for the methodologies and assumptions and paragraph 5 for explanation of negative costs) (high agreement, medium evidence).
o if the climate change damage cost curve grows slowly and regularly, and there is good foresight (which increases the potential for timely adaptation), later and less stringent mitigation is economically justified; o alternatively if the damage cost curve increases steeply, or contains non-linearities (e.g. vulnerability thresholds or even small probabilities of catastrophic events), earlier and more stringent mitigation is economically justified [3.6]. • Climate sensitivity is a key uncertainty for mitigation scenarios that aim to meet a specific temperature level. Studies show that if climate sensitivity is high then the timing and level of mitigation is earlier and more stringent than when it is low [3.5, 3.6]. • Delayed emission reductions lead to investments that lock in more emission-intensive infrastructure and development pathways. This significantly constrains the opportunities to achieve lower stabilization levels (as shown in Table SPM.5) and increases the risk of more severe climate change impacts [3.4, 3.1, 3.5, 3.6]
21. Decision-making about the appropriate level of global mitigation over time involves an iterative risk management process that includes mitigation and adaptation, taking into account actual and avoided climate change damages, co-benefits, sustainability, equity, and attitudes to risk. Choices about the scale and timing of GHG mitigation involve balancing the economic costs of more rapid emission reductions now against the corresponding medium-term and long-term climate risks of delay [high agreement, much evidence]. • Limited and early analytical results from integrated analyses of the costs and benefits of mitigation indicate that these are broadly comparable in magnitude, but do not as yet permit an unambiguous determination of an emissions pathway or stabilization level where benefits exceed costs [3.5].
Table SPM.6: Estimated global macro-economic costs in 2050 relative to the baseline for least-cost trajectories towards different long-term stabilization targetsa) [3.3, 13.3] Range of GDP reductionb), c) (%)
Reduction of average annual GDP growth ratesb), d) (percentage points)
0.5
-1 - 2
<0.05
1.3
slightly negative - 4
<0.1
not available
<5.5
<0.12
Stabilization levels (ppm CO2-eq)
Median GDP reductionb) (%)
590-710 535-590 445-535e)
Notes: a) This corresponds to the full literature across all baselines and mitigation scenarios that provide GDP numbers. b) This is global GDP based market exchange rates. c) The median and the 10th and 90th percentile range of the analyzed data are given. d) The calculation of the reduction of the annual growth rate is based on the average reduction during the period until 2050 that would result in the indicated GDP decrease in 2050. e) The number of studies is relatively small and they generally use low baselines. High emissions baselines generally lead to higher costs.
30 Cost estimates for 2030 are presented in paragraph 5.
18
Summary for Policymakers
E.
Policies, measures and instruments to mitigate climate change
22. A wide variety of national policies and instruments are available to governments to create the incentives for mitigation action. Their applicability depends on national circumstances and an understanding of their interactions, but experience from implementation in various countries and sectors shows there are advantages and disadvantages for any given instrument (high agreement, much evidence). • Four main criteria are used to evaluate policies and instruments: environmental effectiveness, cost effectiveness, distributional effects, including equity, and institutional feasibility [13.2]. • All instruments can be designed well or poorly, and be stringent or lax. In addition, monitoring to improve implementation is an important issue for all instruments. General findings about the performance of policies are: [7.9, 12.2,13.2] o Integrating climate policies in broader development policies makes implementation and overcoming barriers easier. o Regulations and standards generally provide some certainty about emission levels. They may be preferable to other instruments when information or other barriers prevent producers and consumers from responding to price signals. However, they may not induce innovations and more advanced technologies. o Taxes and charges can set a price for carbon, but cannot guarantee a particular level of emissions. Literature identifies taxes as an efficient way of internalizing costs of GHG emissions. o Tradable permits will establish a carbon price. The volume of allowed emissions determines their environmental effectiveness, while the allocation of permits has distributional consequences. Fluctuation in the price of carbon makes it difficult to estimate the total cost of complying with emission permits. o Financial incentives (subsidies and tax credits) are frequently used by governments to stimulate the development and diffusion of new technologies. While economic costs are generally higher than for the instruments listed above, they are often critical to overcome barriers. o Voluntary agreements between industry and governments are politically attractive, raise awareness among stakeholders, and have played a role in the evolution of many national policies. The majority of agreements has not achieved significant emissions reductions beyond business as usual. However, some recent agreements, in a few countries, have accelerated the application of best available technology and led to measurable emission reductions.
o Information instruments (e.g. awareness campaigns) may positively affect environmental quality by promoting informed choices and possibly contributing to behavioural change, however, their impact on emissions has not been measured yet. o RD&D can stimulate technological advances, reduce costs, and enable progress toward stabilization. • Some corporations, local and regional authorities, NGOs and civil groups are adopting a wide variety of voluntary actions. These voluntary actions may limit GHG emissions, stimulate innovative policies, and encourage the deployment of new technologies. On their own, they generally have limited impact on the national or regional level emissions [13.4]. • Lessons learned from specific sector application of national policies and instruments are shown in Table SPM.7. 23. Policies that provide a real or implicit price of carbon could create incentives for producers and consumers to significantly invest in low-GHG products, technologies and processes. Such policies could include economic instruments, government funding and regulation (high agreement, much evidence). • An effective carbon-price signal could realize significant mitigation potential in all sectors [11.3, 13.2]. • Modelling studies, consistent with stabilization at around 550 ppm CO2-eq by 2100 (see Box SPM.3), show carbon prices rising to 20 to 80 US$/tCO2-eq by 2030 and 30 to 155 US$/tCO2-eq by 2050. For the same stabilization level, studies since TAR that take into account induced technological change lower these price ranges to 5 to 65 US$/tCO2-eq in 2030 and 15 to 130 US$/tCO2-eq in 2050 [3.3, 11.4, 11.5]. • Most top-down, as well as some 2050 bottom-up assessments, suggest that real or implicit carbon prices of 20 to 50 US$/tCO2-eq, sustained or increased over decades, could lead to a power generation sector with low-GHG emissions by 2050 and make many mitigation options in the end-use sectors economically attractive. [4.4,11.6] • Barriers to the implementation of mitigation options are manifold and vary by country and sector. They can be related to financial, technological, institutional, informational and behavioural aspects [4.5, 5.5, 6.7, 7.6, 8.6, 9.6, 10.5].
19
Summary for Policymakers
Table SPM.7: Selected sectoral policies, measures and instruments that have shown to be environmentally effective in the respective sector in at least a number of national cases. Sector
Policiesa), measures and instruments shown to be environmentally effective
Key constraints or opportunities
Energy supply [4.5]
Reduction of fossil fuel subsidies
Resistance by vested interests may make them difficult to implement
Taxes or carbon charges on fossil fuels Feed-in tariffs for renewable energy technologies
May be appropriate to create markets for low emissions technologies
Renewable energy obligations Producer subsidies Transport [5.5]
Mandatory fuel economy, biofuel blending and CO2 standards for road transport
Partial coverage of vehicle fleet may limit effectiveness
Taxes on vehicle purchase, registration, use and motor fuels, road and parking pricing
Effectiveness may drop with higher incomes
Influence mobility needs through land use regulations, and infrastructure planning
Particularly appropriate for countries that are building up their transportation systems
Investment in attractive public transport facilities and nonmotorised forms of transport Buildings [6.8]
Industry [7.9]
Appliance standards and labelling
Periodic revision of standards needed
Building codes and certification
Attractive for new buildings. Enforcement can be difficult
Demand-side management programmes
Need for regulations so that utilities may profit
Public sector leadership programmes, including procurement
Government purchasing can expand demand for energyefficient products
Incentives for energy service companies (ESCOs)
Success factor: Access to third party financing
Provision of benchmark information
May be appropriate to stimulate technology uptake. Stability of national policy important in view of international competitiveness
Performance standards Subsidies, tax credits Tradable permits
Predictable allocation mechanisms and stable price signals important for investments
Voluntary agreements
Success factors include: clear targets, a baseline scenario, third party involvement in design and review and formal provisions of monitoring, close cooperation between government and industry
Agriculture [8.6, 8.7, 8.8]
Financial incentives and regulations for improved land management, maintaining soil carbon content, efficient use of fertilizers and irrigation
May encourage synergy with sustainable development and with reducing vulnerability to climate change, thereby overcoming barriers to implementation
Forestry/ forests [9.6]
Financial incentives (national and international) to increase forest area, to reduce deforestation, and to maintain and manage forests
Constraints include lack of investment capital and land tenure issues. Can help poverty alleviation
Land use regulation and enforcement Waste management [10.5]
Financial incentives for improved waste and wastewater management
May stimulate technology diffusion
Renewable energy incentives or obligations
Local availability of low-cost fuel
Waste management regulations
Most effectively applied at national level with enforcement strategies
Note: a) Public RD & D investment in low emissions technologies have proven to be effective in all sectors
24. Government support through financial contributions, tax credits, standard setting and market creation is important for effective technology development, innovation and deployment. Transfer of technology to developing countries depends on enabling conditions and financing (high agreement, much evidence). • Public benefits of RD&D investments are bigger than 20
the benefits captured by the private sector, justifying government support of RD&D. • Government funding in real absolute terms for most energy research programmes has been flat or declining for nearly two decades (even after the UNFCCC came into force) and is now about half of the 1980 level [2.7, 3.4, 4.5, 11.5, 13.2].
Summary for Policymakers
• Governments have a crucial supportive role in providing appropriate enabling environment, such as, institutional, policy, legal and regulatory frameworks31, to sustain investment flows and for effective technology transfer – without which it may be difficult to achieve emission reductions at a significant scale. Mobilizing financing of incremental costs of low-carbon technologies is important. International technology agreements could strengthen the knowledge infrastructure [13.3]. • The potential beneficial effect of technology transfer to developing countries brought about by Annex I countries action may be substantial, but no reliable estimates are available [11.7]. • Financial flows to developing countries through Clean Development Mechanism (CDM) projects have the potential to reach levels of the order of several billions US$ per year32, which is higher than the flows through the Global Environment Facility (GEF), comparable to the energy oriented development assistance flows, but at least an order of magnitude lower than total foreign direct investment flows. The financial flows through CDM, GEF and development assistance for technology transfer have so far been limited and geographically unequally distributed [12.3, 13.3]. 25. Notable achievements of the UNFCCC and its Kyoto Protocol are the establishment of a global response to the climate problem, stimulation of an array of national policies, the creation of an international carbon market and the establishment of new institutional mechanisms that may provide the foundation for future mitigation efforts (high agreement, much evidence). • The impact of the Protocol’s first commitment period relative to global emissions is projected to be limited. Its economic impacts on participating Annex-B countries are projected to be smaller than presented in TAR, that showed 0.2-2% lower GDP in 2012 without emissions trading, and 0.1-1.1% lower GDP with emissions trading among Annex-B countries [1.4, 11.4, 13.3]. 26. The literature identifies many options for achieving reductions of global GHG emissions at the international level through cooperation. It also suggests that successful agreements are environmentally effective, cost-effective, incorporate distributional considerations and equity, and are institutionally feasible (high agreement, much evidence). • Greater cooperative efforts to reduce emissions will help to reduce global costs for achieving a given level of mitigation, or will improve environmental effectiveness [13.3]. • Improving, and expanding the scope of, market mechanisms (such as emission trading, Joint
Implementation and CDM) could reduce overall mitigation costs [13.3]. • Efforts to address climate change can include diverse elements such as emissions targets; sectoral, local, subnational and regional actions; RD&D programmes; adopting common policies; implementing development oriented actions; or expanding financing instruments. These elements can be implemented in an integrated fashion, but comparing the efforts made by different countries quantitatively would be complex and resource intensive [13.3]. • Actions that could be taken by participating countries can be differentiated both in terms of when such action is undertaken, who participates and what the action will be. Actions can be binding or non-binding, include fixed or dynamic targets, and participation can be static or vary over time [13.3].
F.
Sustainable development and climate change mitigation
27. Making development more sustainable by changing development paths can make a major contribution to climate change mitigation, but implementation may require resources to overcome multiple barriers. There is a growing understanding of the possibilities to choose and implement mitigation options in several sectors to realize synergies and avoid conflicts with other dimensions of sustainable development (high agreement, much evidence). • Irrespective of the scale of mitigation measures, adaptation measures are necessary [1.2]. • Addressing climate change can be considered an integral element of sustainable development policies. National circumstances and the strengths of institutions determine how development policies impact GHG emissions. Changes in development paths emerge from the interactions of public and private decision processes involving government, business and civil society, many of which are not traditionally considered as climate policy. This process is most effective when actors participate equitably and decentralized decision making processes are coordinated [2.2, 3.3, 12.2]. • Climate change and other sustainable development policies are often but not always synergistic. There is growing evidence that decisions about macroeconomic policy, agricultural policy, multilateral development bank lending, insurance practices, electricity market reform, energy security and forest conservation, for example, which are often treated as being apart from
31 See the IPCC Special Report on Methodological and Technological Issues in Technology Transfer. 32 Depends strongly on the market price that has fluctuated between 4 and 26 US$/tCO2-eq and based on approximately 1000 CDM proposed plus registered projects likely to generate more than 1.3 billion emission reduction credits before 2012.
21
Summary for Policymakers
•
•
•
•
22
climate policy, can significantly reduce emissions. On the other hand, decisions about improving rural access to modern energy sources for example may not have much influence on global GHG emissions [12.2]. Climate change policies related to energy efficiency and renewable energy are often economically beneficial, improve energy security and reduce local pollutant emissions. Other energy supply mitigation options can be designed to also achieve sustainable development benefits such as avoided displacement of local populations, job creation, and health benefits [4.5,12.3]. Reducing both loss of natural habitat and deforestation can have significant biodiversity, soil and water conservation benefits, and can be implemented in a socially and economically sustainable manner. Forestation and bioenergy plantations can lead to restoration of degraded land, manage water runoff, retain soil carbon and benefit rural economies, but could compete with land for food production and may be negative for biodiversity, if not properly designed [9.7, 12.3]. There are also good possibilities for reinforcing sustainable development through mitigation actions in the waste management, transportation and buildings sectors [5.4, 6.6, 10.5, 12.3]. Making development more sustainable can enhance both mitigative and adaptive capacity, and reduce emissions and vulnerability to climate change. Synergies between mitigation and adaptation can exist, for example properly designed biomass production, formation of protected areas, land management, energy use in buildings and forestry. In other situations, there may be trade-offs, such as increased GHG emissions due to increased consumption of energy related to adaptive responses [2.5, 3.5, 4.5, 6.9, 7.8, 8.5, 9.5, 11.9, 12.1].
G.
Gaps in knowledge
28. There are still relevant gaps in currently available knowledge regarding some aspects of mitigation of climate change, especially in developing countries. Additional research addressing those gaps would further reduce uncertainties and thus facilitate decision-making related to mitigation of climate change [TS.14].
Summary for Policymakers
E Endbox 1: Uncertainty representation Uncertainty is an inherent feature of any assessment. The fourth assessment report clarifies the uncertainties associated with essential statements. Fundamental differences between the underlying disciplinary sciences of the three Working Group reports make a common approach impractical. The “likelihood” approach applied in “Climate change 2007, the physical science basis” and the “confidence” and “likelihood” approaches used in “Climate change 2007, impacts, adaptation, and vulnerability” were judged to be inadequate to deal with the specific uncertainties involved in this mitigation report, as here human choices are considered. In this report a two-dimensional scale is used for the treatment of uncertainty. The scale is based on the expert judgment of the authors of WGIII on the level of concurrence in the literature on a particular finding (level of agreement), and the number and quality of independent sources qualifying under the IPCC rules upon which the finding is based (amount of evidence1) (see Table SPM.E.1). This is not a quantitative approach, from which probabilities relating to uncertainty can be derived. Table SPM.E.1: Qualitative definition of uncertainty
Level of agreement (on a particular finding)
High agreement, limited evidence
High agreement, medium evidence
High agreement, much evidence
Medium agreement, limited evidence
Medium agreement, medium evidence
Medium agreement, much evidence
Low agreement, limited evidence
Low agreement, medium evidence
Low agreement, much evidence
Amount of evidence33 (number and quality of independent sources)
Because the future is inherently uncertain, scenarios i.e. internally consistent images of different futures - not predictions of the future - have been used extensively in this report.
33 “Evidence” in this report is defined as: Information or signs indicating whether a belief or proposition is true or valid. See Glossary.
23
Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
Technical Summary Authors: Terry Barker (UK), Igor Bashmakov (Russia), Lenny Bernstein (USA), Jean E. Bogner (USA), Peter Bosch (The Netherlands), Rutu Dave (The Netherlands), Ogunlade Davidson (Sierra Leone), Brian S. Fisher (Australia), Sujata Gupta (India), Kirsten Halsnæs (Denmark), BertJan Heij (The Netherlands), Suzana Kahn Ribeiro (Brazil), Shigeki Kobayashi (Japan), Mark D. Levine (USA), Daniel L. Martino (Uruguay), Omar Masera (Mexico), Bert Metz (The Netherlands), Leo Meyer (The Netherlands), Gert-Jan Nabuurs (The Netherlands), Adil Najam (Pakistan), Nebojsa Nakicenovic (Austria/Montenegro), Hans-Holger Rogner (Germany), Joyashree Roy (India), Jayant Sathaye (USA), Robert Schock (USA), Priayadarshi Shukla (India), Ralph E. H. Sims (New Zealand), Pete Smith (UK), Dennis A. Tirpak (USA), Diana Urge-Vorsatz (Hungary), Dadi Zhou (PR China)
Review Editor: Mukiri wa Githendu (Kenya)
This Technical Summary should be cited as: Barker T., I. Bashmakov, L. Bernstein, J. E. Bogner, P. R. Bosch, R. Dave, O. R. Davidson, B. S. Fisher, S. Gupta, K. Halsnæs, G.J. Heij, S. Kahn Ribeiro, S. Kobayashi, M. D. Levine, D. L. Martino, O. Masera, B. Metz, L. A. Meyer, G.-J. Nabuurs, A. Najam, N. Nakicenovic, H. -H. Rogner, J. Roy, J. Sathaye, R. Schock, P. Shukla, R. E. H. Sims, P. Smith, D. A. Tirpak, D. Urge-Vorsatz, D. Zhou, 2007: Technical Summary. In: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O. R. Davidson, P. R. Bosch, R. Dave, L. A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Technical Summary
Table of contents
26
1
Introduction ........................................................ 27
2
Framing issues ................................................... 33
3
Issues related to mitigation in the long-term context ................................................................. 37
4
Energy supply .................................................... 43
5
Transport and its infrastructure ................... 48
6
Residential and commercial buildings ......... 53
7
Industry ............................................................... 58
8
Agriculture .......................................................... 63
9
Forestry................................................................ 67
10
Waste management ........................................... 71
11
Mitigation from a cross-sectoral perspective .......................................................... 76
12
Sustainable development and mitigation .... 81
13
Policies, instruments and cooperative agreements .......................................................... 87
14
Gaps in knowledge ............................................ 92
Technical Summary
1
Introduction
Structure of the report, the rationale behind it, the role of cross-cutting themes and framing issues The main aim of this report is to assess options for mitigating climate change. Several aspects link climate change with development issues. This report explores these links in detail, and illustrates where climate change and sustainable development are mutually reinforcing. Economic development needs, resource endowments and mitigative and adaptive capacities differ across regions. There is no one-size-fits-all approach to the climate change problem, and solutions need to be regionally differentiated to reflect different socio-economic conditions and, to a lesser extent, geographical differences. Although this report has a global focus, an attempt is made to differentiate the assessment of scientific and technical findings for the various regions. Given that mitigation options vary significantly between economic sectors, it was decided to use the economic sectors to organize the material on short- to medium-term mitigation options. Contrary to what was done in the Third Assessment Report, all relevant aspects of sectoral mitigation options, such as technology, cost, policies etc., are discussed together, to provide the user with a comprehensive discussion of the sectoral mitigation options. Consequently, the report has four parts. Part A (Chapters 1 and 2) includes the introduction and sets out the frameworks to describe mitigation of climate change in the context of other policies and decision-making. It introduces important concepts (e.g., risk and uncertainty, mitigation and adaptation relationships, distributional and equity aspects and regional integration) and defines important terms used throughout the report. Part B (Chapter 3) assesses long-term stabilization targets, how to get there and what the associated costs are, by examining mitigation scenarios for ranges of stability targets. The relation between adaptation, mitigation and climate change damage avoided is also discussed, in the light of decision-making regarding stabilization (Art. 2 UNFCCC). Part C (Chapters 4–10) focuses on the detailed description of the various sectors responsible for greenhouse gas (GHG) emissions, the short- to medium-term mitigation options and costs in these sectors, the policies for achieving mitigation, the barriers to getting there and the relationship with adaptation and other policies that affect GHG emissions. Part D (Chapters 11–13) assesses cross-sectoral issues, sustainable development and national and international aspects. Chapter 11 covers the aggregated mitigation potential, macro-economic impacts, technology development and transfer, synergies, and trade-offs with other policies and cross-border influences (or spill-over effects). Chapter 12 links climate mitigation with sustainable development. Chapter 13 assesses domestic climate policies and various forms of international cooperation. This Technical Summary has an additional Chapter 14, which deals with gaps in knowledge.
Past, present and future: emission trends Emissions of the GHGs covered by the Kyoto Protocol increased by about 70% (from 28.7 to. 49.0 GtCO2-eq) from 1970–2004 (by 24% from 1990–2004), with carbon dioxide (CO2) being the largest source, having grown by about 80% (see Figure TS.1). The largest growth in CO2 emissions has come from power generation and road transport. Methane (CH4) emissions rose by about 40% from 1970, with an 85% increase from the combustion and use of fossil fuels. Agriculture, however, is the largest source of CH4 emissions. Nitrous oxide (N2O) emissions grew by about 50%, due mainly to increased use of fertilizer and the growth of agriculture. Industrial emission of N2O fell during this period (high agreement, much evidence) [1.3]. Emissions of ozone-depleting substances (ODS) controlled under the Montreal Protocol (which includes GHGs chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs)), increased from a low level in 1970 to about 7.5 GtCO2-eq in 1990 (about 20% of total GHG emissions, not shown in the Figure TS.1), but then decreased to about 1.5 GtCO2-eq in 2004, and are projected to decrease further due to the phase-out of CFCs in developing countries. Emissions of the fluorinated gases (F-gases) (hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and SF6) controlled under the Kyoto Protocol grew rapidly (primarily HFCs) during the 1990s as they replaced ODS to a substantial extent and were estimated at about 0.5 GtCO2eq in 2004 (about 1.1% of total emissions on a 100-year global warming potential (GWP) basis) (high agreement, much evidence) [1.3]. Atmospheric CO2 concentrations have increased by almost 100 ppm since their pre-industrial level, reaching 379 ppm in 2005, with mean annual growth rates in the 2000-2005 period higher than in the 1990s. The total CO2-equivalent (CO2-eq) concentration of all long-lived GHGs is now about 455 ppm CO2-eq. Incorporating the cooling effect of aerosols, other air pollutants and gases released from land-use change into the equivalent concentration, leads to an effective 311-435 ppm CO2-eq concentration (high agreement, much evidence). Considerable uncertainties still surround the estimates of anthropogenic aerosol emissions. As regards global sulphur emissions, these appear to have declined from 75 ± 10 MtS in 1990 to 55-62 MtS in 2000. Data on non-sulphur aerosols are sparse and highly speculative. (medium agreement, medium evidence). In 2004, energy supply accounted for about 26% of GHG emissions, industry 19%, gases released from land-use change and forestry 17%, agriculture 14%, transport 13%, residential, commercial and service sectors 8% and waste 3% (see Figure TS.2). These figures should be seen as indicative, as some uncertainty remains, particularly with regards to CH4 and N2O emissions (error margin estimated to be in the order of 30-50%) and CO2 emissions from agriculture and forestry with an even higher error margin (high agreement, medium evidence) [1.3]. 27
Technical Summary
5
Gt CO2eq/yr HFCs, PFCs, SF6
0 5
N2O other1) N2O agriculture
0 10
CH4 other2) CH4 waste
5
CH4 agriculture
Notes: 1) Other N O includes industrial processes, deforestation/ savannah burning, 2 waste water and waste incineration. 2) Other is CH from industrial processes and savannah burning. 4 3) Including emissions from bioenergy production and use 4) CO emissions from decay (decomposition) of above ground biomass that 2 remains after logging and deforestation and CO2 from peat fires and decay of drained peat soils. 5) As well as traditional biomass use at 10% of total, assuming 90% is from sustainable biomass production. Corrected for the 10% of carbon in biomass that is assumed to remain as charcoal after combustion. 6) For large-scale forest and scrubland biomass burning averaged data for 19972002 based on Global Fire Emissions Data base satellite data. 7) Cement production and natural gas flaring. 8) Fossil fuel use includes emissions from feedstocks.
CH4 energy3)
0 10 5
CO2 decay and peat4)
0
CO2 deforestation5) 6)
30
CO2 other7)
25 20 15
CO2 fossil fuel use8) N 2O 7.9%
10
F-gases 1.1%
5 CH4 14.3%
0 1970
1980
1990 2000 2004
50 CO2 fossil fuel use 56.6%
40 30
Total GHG CO2 (deforestation, decay of biomass, etc) 17.3%
20 10 0 1970
1980
1990
2000 2004
Figure TS.1a: Global anthropogenic greenhouse gas emissions, 1970–2004. One hundred year global warming potentials (GWPs) from IPCC 1996 (SAR) were used to convert emissions to CO2-eq. (see the UNFCCC reporting guidelines). Gases are those reported under UNFCCC reporting guidelines. The uncertainty in the graph is quite large for CH4 and N2O (in the order of 30-50%) and even larger for CO2 from agriculture and forestry. [Figure 1.1a].
28
CO2 (other) 2.8% Figure TS.1b: Global anthropogenic greenhousegas emissions in 2004 [Figure 1.1b].
Technical Summary
14
Gt CO2-eq. F-gases N2 O
12
CH4 CO2
10
8
6
4
2
0
1990 2004 Energy supply 1)
1990 2004 Transport 2)
1990 2004 Residential and commercial buildings 3)
1990 2004 Industry 4)
Figure TS.2a: GHG emissions by sector in 1990 and 2004 100-year GWPs from IPCC 1996 (Second Assessment Report (SAR)) were used to convert emissions to CO2-eq. The uncertainty in the graph is quite large for CH4 and N2O (in the order of 30–50%) and even larger for CO2 from agriculture and forestry. For large-scale biomass burning, averaged activity data for 1997–2002 were used from Global Fire Emissions Database based on satellite data. Peat (fire and decay) emissions are based on recent data from WL/Delft Hydraulics. [Figure 1.3a]
Waste and wastewater7) 2.8% Energy supply1) 25.9%
Forestry6) 17.4%
Agriculture5) 13.5%
1990 2004 Agriculture 5)
1990 2004 LULUCF/ Forestry 6)
1990 2004 Waste and wastewater 7)
Notes to Figure TS.2a and 2b: 1) Excluding refineries, coke ovens etc., which are included in industry. 2) Including international transport (bunkers), excluding fisheries. Excluding offroad agricultural and forestry vehicles and machinery. 3) Including traditional biomass use. Emissions in Chapter 6 are also reported on the basis of end-use allocation (including the sector’s share in emissions caused by centralized electricity generation) so that any mitigation achievements in the sector resulting from lower electricity use are credited to the sector. 4) Including refineries, coke ovens etc. Emissions reported in Chapter 7 are also reported on the basis of end-use allocation (including the sector’s share in emissions caused by centralized electricity generation) so that any mitigation achievements in the sector resulting from lower electricity use are credited to the sector. 5) Including agricultural waste burning and savannah burning (non-CO ). CO 2 2 emissions and/or removals from agricultural soils are not estimated in this database. 6) Data include CO emissions from deforestation, CO emissions from decay 2 2 (decomposition) of above-ground biomass that remains after logging and deforestation, and CO2 from peat fires and decay of drained peat soils. Chapter 9 reports emissions from deforestation only. 7) Includes landfill CH , wastewater CH and N O, and CO from waste incineration 4 4 2 2 (fossil carbon only).
Transport2) 13.1%
Industry4) 19.4%
Residential and commercial buildings3) 7.9%
Figure TS.2b: GHG emissions by sector in 2004 [Figure 1.3b].
29
Technical Summary
Figure TS.3 identifies the individual contributions to energyrelated CO2 emissions from changes in population, income per capita (gross domestic product (GDP) expressed in terms of purchasing-power parity per person - GDPppp/cap1), energy intensity (Total Primary Energy Supply (TPES)/GDPppp), and carbon intensity (CO2/TPES). Some of these factors boost CO2 emissions (bars above the zero line), while others lower them (bar below the zero line). The actual change in emissions per decade is shown by the dashed black lines. According to Figure TS.3, the increase in population and GDP-ppp/cap (and therefore energy use per capita) have outweighed and are projected to continue to outweigh the decrease in energy intensities (TPES/ GDPppp) and conceal the fact that CO2 emissions per unit of GDPppp are 40% lower today than during the early 1970s and have declined faster than primary energy per unit of GDPppp or CO2 per unit of primary energy. The carbon intensity of energy supply (CO2/TPES) had an offsetting effect on CO2 emissions between the mid 1980s and 2000, but has since been increasing and is projected to have no such effect after 2010 (high agreement, much evidence) [1.3]. In 2004, Annex I countries had 20% of the world’s population, but accounted for 46% of global GHG emissions, and the 80% in Non-Annex I countries for only 54%. The contrast between the region with the highest per capita GHG emissions (North America) and the lowest (Non-Annex I South Asia) is even more pronounced (see Figure TS.4a): 5% of the world’s population (North America) emits 19.4%,
14
while 30.3% (Non-Annex I South Asia) emits 13.1%. A different picture emerges if the metric GHG emissions per unit of GDPppp is used (see Figure TS.4b). In these terms, Annex I countries generated 57% of gross world product with a GHG intensity of production of 0.68 kg CO2-eq/US$ GDPppp (non-Annex I countries 1.06 kg CO2-eq/US$ GDPppp) (high agreement, much evidence) [1.3]. Global energy use and supply – the main drivers of GHG emissions – is projected to continue to grow, especially as developing countries pursue industrialization. Should there be no change in energy policies, the energy mix supplied to run the global economy in the 2025–30 timeframe will essentially remain unchanged, with more than 80% of energy supply based on fossil fuels with consequent implications for GHG emissions. On this basis, the projected emissions of energy-related CO2 in 2030 are 40–110% higher than in 2000, with two thirds to three quarters of this increase originating in non-Annex I countries, though per capita emissions in developed countries will remain substantially higher, that is 9.6 tCO2/cap to 15.1 tCO2/cap in Annex I regions versus 2.8 tCO2/cap to 5.1 tCO2/cap in non-Annex I regions (high agreement, much evidence) [1.3]. For 2030, projections of total GHG emissions (Kyoto gases) consistently show an increase of 25–90% compared with 2000, with more recent projections higher than earlier ones (high agreement, much evidence).
Gt CO2 observations
scenarios
12 10 8 Population 6 4
Income per capita (GDP-ppp/Pop)
2
Net change Carbon intensity (CO2/TPES)
0 -2
Energy intensity (TPES/GDP-ppp)
-4 -6 -8 1970-80
1980-90
1990-2000
2000-10
2010-20
2020-30
Figure TS.3: Decomposition of global energy-related CO2 emission changes at the global scale for three past and three future decades [Figure 1.6].
1
30
The GDPppp metric is used for illustrative purposes only for this report.
Technical Summary
For 2100, the SRES2 range (a 40% decline to 250% increase compared with 2000) is still valid. More recent projections tend to be higher: increase of 90% to 250% compared with 2000 (see Figure TS.5). Scenarios that account for climate policies, whose implementation is currently under discussion, also show global emissions rising for many decades. Developing countries (e.g., Brazil, China, India and Mexico) that have undertaken efforts for reasons other than climate change have reduced their emissions growth over the past three decades by approximately 500 million tonnes CO2 per year; that is, more than the reductions required from Annex I countries by the Kyoto Protocol. Many of these efforts are motivated by economic development and poverty alleviation, energy security and local environmental protection. The most promising policy approaches, therefore, seem to be those that capitalize on natural synergies between climate protection and development priorities to advance both simultaneously (high agreement, medium evidence) [1.3].
The first addition to the treaty, the Kyoto Protocol, was adopted in 1997 and entered into force in February 2005. As of February 2007, 168 states and the European Economic Community have ratified the Protocol. Under Article 3.1 of the Kyoto Protocol, Annex I Parties in aggregate agreed to reduce
3.0 Non-Annex I: Population 80.3%
2.5
25
Annex I non-Annex I
2.0
20
0 0
1,000
Middle East: 3.8%
5
Other non-Annex I: 2.0% Europe Annex II: and M & T 11,4%
10
JANZ: 5.2%
USA & Canada: 19,4%
15
EIT Annex I: 9.7%
Average Annex I: 16,1 t CO2eq/cap
Latin America & Carribean: 10.3%
Non-Annex I East Asia: 17,3%
Africa: 7.8%
South Asia:13,1%
2,000 3,000 4,000 5,000 Cumulative population in million
6,000
Figure TS.4a: Distribution of regional per capita GHG emissions (all Kyoto gases including those from land-use) over the population of different country groupings in 2004. The percentages in the bars indicate a region’s share in global GHG emissions [Figure 1.4a].
0.5
Non-Annex I East Asia: 17,3%
0 7,000
GHG/GDP kg CO2eq/US$ 0.683 1.055
1.5 1.0
Average non-Annex I: 4,2 t CO2eq/cap
Share in global GDP 56.6% 43.4%
Other non-Annex I: 2.0%
Middle East: 3.8% Latin America & Carribean: 10.3%
Annex I: Population 19.7%
kg CO2eq/US$ GDPppp (2000)
Africa: 7.8%
30
t CO2eq/cap
The United Nations Framework Convention on Climate Change (UNFCCC) is the main vehicle for promoting international responses to climate change. It entered into force in March 1994 and has achieved near universal ratification – 189 of the 194 UN member states (December 2006). A Dialogue on Long-Term Cooperation Action to Address Climate Change by Enhancing Implementation of the Convention was set up at CMP13 in 2005, taking the form of an open and non-binding exchange of views and information in support of enhanced implementation of the Convention.
EIT Annex I: 9.7%
35
International response
0
10,000
South Asia: 13,1%
USA & Canada: 19,4%
JANZ: 5.2%
Europe Annex II and M & T: 11,4%
20,000 30,000 40,000 50,000 Cumulative GDPppp (2000) in billion US$
60,000
Figure TS.4b: Distribution of regional GHG emissions (all Kyoto gases including those from land-use) per US$ of GDPppp over the GDP of different country groupings in 2004. The percentages in the bars indicate a region’s share in global GHG emissions [Figure 1.4b].
Note: Countries are grouped according to the classification of the UNFCCC and its Kyoto Protocol; this means that countries that have joined the European Union since then are still listed under EIT Annex I. A full set of data for all countries for 2004 was not available. The countries in each of the regional groupings include: • EIT Annex I: Belarus, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Russian Federation, Slovakia, Slovenia, Ukraine • Europe Annex II & M&T: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom; Monaco and Turkey • JANZ: Japan, Australia, New Zealand. • Middle East: Bahrain, Islamic Republic of Iran, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, United Arab Emirates, Yemen • Latin America & the Caribbean: Antigua & Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Lucia, St. Kitts-NevisAnguilla, St. Vincent-Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela • Non-Annex I East Asia: Cambodia, China, Korea (DPR), Laos (PDR), Mongolia, Republic of Korea, Viet Nam. • South Asia: Afghanistan, Bangladesh, Bhutan, Comoros, Cook Islands, Fiji, India, Indonesia, Kiribati, Malaysia, Maldives, Marshall Islands, Micronesia, (Federated States of), Myanmar, Nauru, Niue, Nepal, Pakistan, Palau, Papua New Guinea, Philippine, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu • North America: Canada, United States of America. • Other non-Annex I: Albania, Armenia, Azerbaijan, Bosnia Herzegovina, Cyprus, Georgia, Kazakhstan, Kyrgyzstan, Malta, Moldova, San Marino, Serbia, Tajikistan, Turkmenistan, Uzbekistan, Republic of Macedonia • Africa: Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Congo, Democratic Republic of Congo, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Togo, Tunisia, Uganda, United Republic of Tanzania, Zambia, Zimbabwe. 2
3
SRES refers to scenarios described in the IPCC Special Report on Emission Scenarios (IPCC, 2000b). The A1 family of scenarios describes a future with very rapid economic growth, low population growth and rapid introduction of new and more efficient technologies. B1 describes a convergent world, with the same global population that peaks in mid century and declines thereafter, with rapid changes in economic structures. B2 describes a world ‘in which emphasis is on local solutions to economic, social, and environmental sustainability’. It features moderate population growth, intermediate levels of economic development, and less rapid and more diverse technological change than the A1B scenario. The Conference of the Parties (COP) is the supreme body of the Convention also serves as the Meeting of the Parties (MOP) for the Protocol. CMP1 is the first meeting of the Conference of the Parties acting as the Meeting of the Parties of the Kyoto Protocol.
31
Technical Summary
180
Gt CO2-eq/yr F-gases
160
N2O
140 120
CH4
100
CO2
80 60 40
2030
post SRES
2100
5th
25th
median
95th
SRES
75th
B1
A1T
B2
A1B
A1FI
A2
5th
25th
median
95th
SRES
75th
B1
B2
A1T
A2
A1B
A1FI
0
2000
20
post SRES
Figure TS.5: Global GHG emissions for 2000 and projected baseline emissions for 2030 and 2100 from IPCC SRES and the post-SRES literature. The figure provides the emissions from the six illustrative SRES scenarios. It also provides the frequency distribution of the emissions in the post-SRES scenarios (5th, 25th, median, 75th, 95th percentile), as covered in Chapter 3. F-gases cover HFCs, PFCs and SF6 [Figure 1.7].
their overall GHG emissions to at least 5% below 1990 levels. The entry into force of the Kyoto Protocol marks a first, though modest, step towards achieving the ultimate objective of the UFCCC to avoid dangerous anthropogenic interference with the climate system. Its full implementation by all the Protocol signatories, however, would still be far from reversing overall global GHG-emission trends. The strengths of the Kyoto Protocol are its provision for market mechanisms such as GHG-emission trading and its institutional architecture. One weakness of the Protocol, however, is its non-ratification by some significant GHG emitters. A new Ad Hoc Working Group (AWG) on the Commitments of Annex I Countries under the Kyoto Protocol beyond 2012 was set up at CMP1, and agreed at CMP2 that the second review of Article 9 of the Kyoto Protocol will take place in 2008. There are also voluntary international initiatives to develop and implement new technologies to reduce GHG emissions. These include: the Carbon Sequestration Leadership Forum (promoting CO2 capture and storage); the Hydrogen partnership; the Methane to Markets Partnership, and the AsiaPacific Partnership for Clean Development and Climate (2005), which includes Australia, USA, Japan, China, India and SouthKorea. Climate change has also become an important growing concern of the G8 since its meeting in Gleneagles, Scotland in 2005. At that meeting, a plan of action was developed which tasked the International Energy Agency, the World Bank and the Renewable Energy and Energy Efficiency Partnership with supporting their efforts. Additionally, Gleneagles created a Clean Energy, Climate Change and Sustainable Development Dialogue process for the largest emitters. The International Energy Agency (IEA) and the World Bank were charged with advising that dialogue process [1.4]. 32
Article 2 of the Convention and mitigation Article 2 of the UNFCCC requires that dangerous interference with the climate system be prevented and hence the stabilization of atmospheric GHG concentrations at levels and within a time frame that would achieve this objective. The criteria in Article 2 that specify (risks of) dangerous anthropogenic climate change include: food security, protection of ecosystems and sustainable economic development. Implementing Article 2 implies dealing with a number of complex issues: What level of climate change is dangerous? Decisions made in relation to Article 2 would determine the level of climate change that is set as the goal for policy, and have fundamental implications for emission-reduction pathways as well as the scale of adaptation required. Choosing a stabilization level implies balancing the risks of climate change (from gradual change and extreme events, and irreversible change of the climate, including those to food security, ecosystems and sustainable development) against the risks of response measures that may threaten economic sustainability. Although any judgment on ‘dangerous interference’ is necessarily a social and political one, depending on the level of risk deemed acceptable, large emission reductions are unavoidable if stabilization is to be achieved. The lower the stabilization level, the earlier these large reductions have to be realized (high agreement, much evidence) [1.2]. Sustainable development: Projected anthropogenic climate change appears likely to adversely affect sustainable development, with the effects tending to increase with higher GHG concentrations (WGII AR4, Chapter 19). Properly designed climate change responses
Technical Summary
can be an integral part of sustainable development and the two can be mutually reinforcing. Mitigation of climate change can conserve or enhance natural capital (ecosystems, the environment as sources and sinks for economic activities) and prevent or avoid damage to human systems and, thereby contribute to the overall productivity of capital needed for socio-economic development, including mitigative and adaptive capacity. In turn, sustainable development paths can reduce vulnerability to climate change and reduce GHG emissions (medium agreement, much evidence) [1.2]. Distributional issues: Climate change is subject to a very asymmetric distribution of present emissions and future impacts and vulnerabilities. Equity can be elaborated in terms of distributing the costs of mitigation or adaptation, distributing future emission rights and ensuring institutional and procedural fairness. Because the industrialized nations are the source of most past and current GHG emissions and have the technical and financial capability to act, the Convention places the heaviest burden for the first steps in mitigating climate change on them. This is enshrined in the principle of ‘common but differentiated responsibilities’ (high agreement, much evidence) [1.2]. Timing: Due to the inertia of both climate and socio-economic systems, the benefits of mitigation actions initiated now may result in significant avoided climate change only after several decades. This means that mitigation actions need to start in the short term in order to have medium- and longer-term benefits and to avoid lock-in of carbon-intensive technologies (high agreement, much evidence) [1.2]. Mitigation and adaptation: Adaptation and mitigation are two types of policy response to climate change, which can be complementary, substitutable or independent of each other. Irrespective of the scale of mitigation measures, adaptation measures will be required anyway, due to the inertia in the climate system. Over the next 20 years or so, even the most aggressive climate policy can do little to avoid warming already ‘loaded’ into the climate system. The benefits of avoided climate change will only accrue beyond that time. Over longer time frames, beyond the next few decades, mitigation investments have a greater potential to avoid climate change damage and this potential is larger than the adaptation options that can currently be envisaged (medium agreement, medium evidence) [1.2]. Risk and uncertainty: An important aspect in the implementation of Article 2 is the uncertainty involved in assessing the risk and severity of climate change impacts and evaluating the level of mitigation action (and its costs) needed to reduce the risk. Given this uncertainty, decision-making on the implementation of Article 2 would benefit from the incorporation of riskmanagement principles. A precautionary and anticipatory risk-management approach would incorporate adaptation and
preventive mitigation measures based on the costs and benefits of avoided climate change damage, taking into account the (small) chance of worst-case outcomes (medium agreement, medium evidence) [1.2].
2
Framing issues
Climate change mitigation and sustainable development There is a two-way relationship between climate change and development. On the one hand vulnerability to climate change is framed and strongly influenced by development patterns and income levels. Decisions about technology, investment, trade, poverty, community rights, social policies or governance, which may seem unrelated to climate policy, may have profound impacts on emissions, the extent of mitigation required, and the cost and benefits that result [2.2.3]. On the other hand, climate change itself, and adaptation and mitigation policies could have significant positive impacts on development in the sense that development can be made more sustainable. This leads to the notion that climate change policies can be considered 1) in their own right (‘climate first’); or 2) as an integral element of sustainable-development policies (‘development first’). Framing the debate as a sustainable development problem rather than a solely environmental one may better address the needs of countries, while acknowledging that the driving forces for emissions are linked to the underlying development path [2.2.3]. Development paths evolve as a result of economic and social transactions, which are influenced by government policies, private sector initiatives and by the preferences and choices of consumers. These include a broad number of policies related to nature conservation, legal frameworks, property rights, rule of law, taxes and regulation, production, security and safety of food, consumption patterns, human and institutional capacity building efforts, R&D, financial schemes, technology transfer, energy efficiency and energy options. These policies do not usually emerge and become implemented as part of a general development-policy package, but are normally targeted towards more specific policy goals like air-pollution standards, food security and health issues, GHG-emission reduction, income generation by specific groups,or development of industries for green technologies. However, significant impacts can arise from such policies on sustainability and greenhouse mitigation and the outcomes of adaptation. The strong relationship between mitigation of climate change and development applies in both developed and developing countries. Chapter 12 and to some extent Chapters 4–11 address these issues in more detail [2.2.5; 2.2.7]. Emerging literature has identified methodological approaches to identify, characterize and analyze the interactions between sustainable development and climate change responses. Several 33
Technical Summary
authors have suggested that sustainable development can be addressed as a framework for jointly assessing social, human, environmental and economic dimensions. One way to address these dimensions is to use a number of economic, environmental, human and social indicators to assess the impacts of policies on sustainable development, including both quantitative and qualitative measurement standards (high agreement, limited evidence) [2.2.4]. Decision-making, risk and uncertainty Mitigation policies are developed in response to concerns about the risk of climate change impacts. However, deciding on a proper reaction to these concerns means dealing with uncertainties. Risk refers to cases for which the probability of outcomes and its consequences can be ascertained through well-established theories with reliable, complete data, while uncertainty refers to situations in which the appropriate data may be fragmentary or unavailable. Causes of uncertainty include insufficient or contradictory evidence as well as human behaviour. The human dimensions of uncertainty, especially coordination and strategic behaviour issues, constitute a major part of the uncertainties related to climate change mitigation (high agreement, much evidence) [2.3.3; 2.3.4]. Decision-support analysis can assist decision makers, especially if there is no optimum policy that everybody can agree on. For this, a number of analytical approaches are available, each with their own strengths and weaknesses, which help to keep the information content of the climate change problem within the cognitive limits of the large number of decision makers and support a more informed and effective dialogue among the many parties involved. There are, however,
significant problems in identifying, measuring and quantifying the many variables that are important inputs to any decisionsupport analysis framework – particularly impacts on natural systems and human health that do not have a market value, and for which all approaches are simplifications of the reality (high agreement, much evidence) [2.3.7]. When many decision makers with different value systems are involved in a decision, it is helpful to be as clear as possible about the value judgments underpinning any analytic outcomes they are expected to draw on. This can be particularly difficult and subtle where analysis aims to illuminate choices associated with high levels of uncertainty and risk (medium agreement, medium evidence) [2.3.2; 2.3.7]. Integrated assessments can inform decision makers of the relationship between geophysical climate change, climateimpact predictions, adaptation potentials and the costs of emission reductions and the benefits of avoided climate change damage. These assessments have frameworks to deal with incomplete or imprecise data. To communicate the uncertainties involved, this report uses the terms in Table TS.1 to describe the relative levels of expert agreement on the respective statements in the light of the underlying literature (in rows) and the number and quality of independent sources qualifying under IPCC rules4 upon which a finding is based (in columns). The other approaches of ‘likelihood’ and ‘confidence’ are not used in this report as human choices are concerned, and none of the other approaches used provides sufficient characterization of the uncertainties involved in mitigation (high agreement, much evidence) [2.4].
Table TS.1: Qualitative definition of uncertainty [Table 2.2].
Level of agreement (on a particular finding)
High agreement, limited evidence
High agreement, medium evidence
High agreement, much evidence
Medium agreement, limited evidence
Medium agreement, medium evidence
Medium agreement, much evidence
Low agreement, limited evidence
Low agreement, medium evidence
Low agreement, much evidence
Amount of evidence (number and quality of independent sources)
Note: This table is based on two dimensions of uncertainty: the amount of evidence5 and the level of agreement. The amount of evidence available about a given technology is assessed by examining the number and quality of independent sources of information. The level of agreement expresses the subjective probability of the results being in a certain realm.
4 5
34
IPCC rules permit the use of both peer-reviewed literature and non-peer-reviewed literature that the authors deem to be of equivalent quality. ‘Evidence’ in this report is defined as: Information or signs indicating whether a belief or proposition is true or valid. See Glossary.
Technical Summary
Costs, benefits, concepts including private and social cost perspectives and relationships with other decision-making frameworks There are different ways of defining the potential for mitigation and it is therefore important to specify what potential is meant. ‘Potential’ is used to express the degree of GHG reduction that can be achieved by a mitigation option with a given cost per tonne of carbon avoided over a given period, compared with a baseline or reference case. The measure is usually expressed as million tonnes carbon- or CO2-equivalent emissions avoided compared with baseline emissions [2.4.3]. Market potential is the mitigation potential based on private costs and private discount rates6, which might be expected to occur under forecast market conditions, including policies and measures currently in place, noting that barriers limit actual uptake. Economic potential is the amount of GHG mitigation, which takes into account social costs and benefits and social discount rates7 assuming that market efficiency is improved by policies and measures and barriers are removed. However, current bottom-up and top-down studies of economic potential have limitations in considering life-style choices and in including all externalities such as local air pollution. Technical potential is the amount by which it is possible to reduce GHG emissions by implementing a technology or practice that has already been demonstrated. There is no specific reference to costs here, only to ‘practical constraints’, although implicit economic considerations are taken into account in some cases. (high agreement, much evidence) [2.4.3]. Studies of market potential can be used to inform policy makers about mitigation potential with existing policies and barriers, while studies of economic potentials show what might be achieved if appropriate new and additional policies were put into place to remove barriers and include social costs and benefits. The economic potential is therefore generally greater than the market potential. Mitigation potential is estimated using different types of approaches. There are two broad classes – “bottom-up” and “top-down” approaches, which primarily have been used to assess the economic potential: • Bottom-up studies are based on assessment of mitigation options, emphasizing specific technologies and regulations. They are typically sectoral studies taking the macro-economy as unchanged. Sector estimates have been aggregated, as in the TAR, to provide an estimate of global mitigation potential for this assessment. • Top-down studies assess the economy-wide potential of mitigation options. They use globally consistent frameworks 6 7
and aggregated information about mitigation options and capture macro-economic and market feedbacks. Bottom-up studies in particular are useful for the assessment of specific policy options at sectoral level, e.g. options for improving energy efficiency, while top-down studies are useful for assessing cross-sectoral and economy-wide climate change policies, such as carbon taxes and stabilization policies. Bottomup and top-down models have become more similar since the TAR as top-down models have incorporated more technological mitigation options (see Chapter 11) and bottom-up models have incorporated more macroeconomic and market feedbacks as well as adopting barrier analysis into their model structures. Mitigation and adaptation relationships; capacities and policies Climate change mitigation and adaptation have some common elements, they may be complementary, substitutable, independent or competitive in dealing with climate change, and also have very different characteristics and timescales [2.5]. Both adaptation and mitigation make demands on the capacity of societies, which are intimately connected to social and economic development. The responses to climate change depend on exposure to climate risk, society’s natural and manmade capital assets, human capital and institutions as well as income. Together these will define a society’s adaptive and mitigative capacities. Policies that support development and those that enhance its adaptive and mitigative capacities may, but need not, have much in common. Policies may be chosen to have synergetic impacts on the natural system and the socio-economic system but difficult trade-offs may sometimes have to be made. Key factors that determine the capacity of individual stakeholders and societies to implement climate change mitigation and adaptation include: access to resources; markets; finance; information, and a number of governance issues (medium agreement, limited evidence) [2.5.2]. Distributional and equity aspects Decisions on climate change have large implications for local, national, inter-regional and intergenerational equity, and the application of different equity approaches has major implications for policy recommendations as well as for the distribution of the costs and benefits of climate policies [2.6]. Different approaches to social justice can be applied to the evaluation of the equity consequences of climate change policies. As the IPCC Third Assessment Report (TAR) suggested, given strong subjective preferences for certain equity principles among different stakeholders, it is more effective to look for practical approaches that combine equity principles. Equity approaches vary from traditional economic approaches to rights-
Private costs and discount rates reflect the perspective of private consumers and companies; see Glossary for a fuller description. Social costs and discount rates reflect the perspective of society. Social discount rates are lower than those used by private investors; see Glossary for a fuller description.
35
Technical Summary
Public sector incentives, standards, regulation, subsidies, taxes
funding
Market DemandPull Pull Market //Demand From: Disembodied Technology (Knowledge)
Basic R&D
Applied R&D
Demonstration
Niche markets
Diffusion
To: Embodied Technology (plant, equipment,..)
the uncertainty about the performance of individual options. Climate policies are not the only determinant of technological change. However, a review of future scenarios (see Chapter 3) indicates that the overall rate of change of technologies in the absence of climate policies might be as large as, if not larger than, the influence of the climate policies themselves (high agreement, much evidence) [2.7.1].
Product TechnologyPush Push Product //Technology
funding
investments, knowledge and market spillovers
Private sector
Figure TS.6: The technology development cycle and its main driving forces [Figure 2.3]. Note: important overlaps and feedbacks exist between the stylized technology life-cycle phases illustrated here. The figure therefore does not suggest a ‘linear’ model of innovation. It is important to recognize the need for finer terminological distinction of ‘technology’, particularly when discussing different mitigation and adaptation options.
based approaches. An economic approach would be to assess welfare losses and gains to different groups and the society at large, while a rights-based approach would focus on rights, for example, in terms of emissions per capita or GDP allowed for all countries, irrespective of the costs of mitigation or the mitigative capacity. The literature also includes a capability approach that puts the emphasis on opportunities and freedom, which in terms of climate policy can be interpreted as the capacity to mitigate or to adapt or to avoid being vulnerable to climate change (medium agreement, medium evidence) [2.6.3]. Technology research, development, deployment, diffusion and transfer The pace and cost of any response to climate change concerns will also depend critically on the cost, performance, and availability of technologies that can lower emissions in the future, although other factors such as growth in wealth and population are also highly important [2.7]. Technology simultaneously influences the size of the climate change problem and the cost of its solution. Technology is the broad set of competences and tools covering know-how, experience and equipment, used by humans to produce services and transform resources. The principal role of technology in mitigating GHG emissions is in controlling the social cost of limiting the emissions. Many studies show the significant economic value of the improvements in emission-mitigating technologies that are currently in use and the development and deployment of advanced emission-mitigation technologies (high agreement, much evidence) [2.7.1]. A broad portfolio of technologies can be expected to play a role in meeting the goal of the UNFCCC and managing the risk of climate change, because of the need for large emission reductions, the large variation in national circumstances and 36
Technological change is particularly important over the long-term time scales characteristic of climate change. Decadeor century-long time scales are typical for the lags involved between technological innovation and widespread diffusion and of the capital turnover rates characteristic of long-lived energy capital stock and infrastructures. Many approaches are used to split up the process of technological change into distinct phases. One is to consider technological change as roughly a two-part process: 1) conceiving, creating and developing new technologies or enhancing existing technologies – advancing the ‘technological frontier’; 2) the diffusion or deployment of these technologies. Our understanding of technology and its role in addressing climate change is improving continuously. The processes by which technologies are created, developed, deployed and eventually replaced, however, are complex (see Figure TS.6) and no simple descriptions of these processes exist. Technology development and deployment is characterized by two public goods problems. First, the level of R&D is sub-optimal because private decisionmakers cannot capture the full value of private investments. Second, there is a classical environmental externality problem, in that private markets do not reflect the full costs of climate change (high agreement, much evidence) [2.7.2]. Three important sources of technological change are R&D, learning and spill-overs. • R&D encompasses a broad set of activities in which firms, governments or other entities expend resources specifically to gain new knowledge that can be embodied in new or improved technology. • Learning is the aggregate outcome of complex underlying sources of technology advance that frequently include important contributions from R&D, spill-overs and economies of scale. • Spill-overs refer to the transfer of the knowledge or the economic benefits of innovation from one individual, firm, industry or other entity, or from one technology to another. On the whole, empirical and theoretical evidence strongly suggest that all three of these play important roles in technological advance, and there is no compelling reason to believe that one is broadly more important than the others. As spill-overs from other sectors have had an enormous effect on innovation in the energy sector, a robust and broad technological base may be as important for the development of technologies pertinent to climate change as explicit climate change or energy research. A broad portfolio of research is needed, because it is not possible to identify winners and losers ex-ante. The sources of
Technical Summary
technological change are frequently subsumed under the general drivers ‘supply push’ (e.g., via R&D) or ‘demand pull’ (e.g., via learning). These are, however, not simply substitutes, but may have highly complementary interactions (high agreement, much evidence) [2.7.2]. On technology transfer, the main findings of the IPCC Special Report on Methodological and Technological Issues of Technology Transfer (2000) remain valid: that a suitable enabling environment needs to be created in host and recipient countries (high agreement, much evidence) [2.7.3]. Regional Dimensions Climate change studies have used various different regional definitions, depending on the character of the problem considered and differences in methodological approaches. The multitude of possible regional representations hinders the comparability and transfer of information between the various types of studies done for specific regions and scales. This report largely has chosen a pragmatic ways of analysing regional information and presenting findings [2.8].
3
Issues related to mitigation in the long-term context
Baseline scenario drivers Population projections are now generally lower than in the IPCC Special Report on Emission Scenarios (SRES), based on new data indicating that birth rates in many parts of the world have fallen sharply. So far, these new population projections have not been implemented in many of the new emissions scenarios in the literature. The studies that have incorporated them result in more or less the same overall emissions levels, due to changes in other driving factors such as economic growth (high agreement, much evidence) [3.2.1].
literature is very large, ranging from 17 to around 135 GtCO2-eq (4.6-36.8 GtC)8, about the same as the SRES range (Figure TS.7). Different reasons may contribute to the fact that emissions have not declined despite somewhat lower projections for population and GDP. All other factors being equal, lower population projections would result in lower emissions. In the scenarios that use lower projections, however, changes in other drivers of emissions have partly offset the consequences of lower populations. Few studies incorporated lower population projections, but where they did, they showed that lower population is offset by higher rates of economic growth, and/or a shift toward a more carbon-intensive energy system, such as a shift to coal because of increasing oil and gas prices. The majority of scenarios indicate an increase in emissions during most of the century. However, there are some baseline (reference) scenarios both in the new and older literature where emissions peak and then decline (high agreement, much evidence) [3.2.2]. Baseline land-related GHG emissions are projected to increase with growing cropland requirements, but at a slower rate than energy-related emissions. As far as CO2 emissions from land-use change (mostly deforestation) are concerned, post-SRES scenarios show a similar trend to SRES scenarios: a slow decline, possibly leading to zero net emissions by the end of the century. Emissions of non-CO2 GHGs as a group (mostly from agriculture) are projected to increase, but somewhat less rapidly than CO2 emissions, because the most important sources of CH4 and N2O are agricultural activities, and agriculture is growing less than energy use. Emission projections from the recent literature are similar to SRES. Recent non-CO2 GHG emission baseline scenarios suggest that agricultural CH4 and N2O emissions will increase until the end of this century, potentially doubling in some baselines. While the emissions of some fluorinated compounds are projected to decrease, many are expected to grow substantially because of the rapid growth rate of some emitting industries and the replacement of ODS with HFCs (high agreement, medium evidence) [3.2.2].
Economic growth perspectives have not changed much. There is a considerable overlap in the GDP numbers published, with a slight downwards shift of the median of the new scenarios by about 7% compared with the median in the pre-SRES scenario literature. The data suggest no appreciable change in the distribution of GDP projections. Economic growth projections for Africa, Latin America and the Middle East are lower than in the SRES scenarios (high agreement, much evidence) [3.2.1].
Noticeable changes have occurred in projections of the emissions of the aerosol precursors SO2 and NOx since SRES. Recent literature shows a slower short-term growth of these emissions than SRES. As a consequence also the long-term ranges of both emissions sources are lower in the recent literature. Recent scenarios project sulphur emissions to peak earlier and at lower levels than in SRES. A small number of new scenarios have begun to explore emission pathways for black and organic carbon (high agreement, medium evidence) [3.2.2].
Baseline scenario emissions (all gases and sectors) The resulting span of energy-related and industrial CO2 emissions in 2100 across baseline scenarios in the post-SRES
In general, the comparison of SRES and new scenarios in the literature shows that the ranges of the main driving forces and emissions have not changed very much.
8
This is the 5th to 95th percentile of the full distribution
37
Technical Summary
post-SRES non-intervention
200 150 100 50 0 -50 1940
1960
1980
2000
2020
2040
2060
2080
SRES+pre-SRES non-intervention
250
2100
Figure TS.7: Comparison of the SRES and pre-SRES energy-related and industrial CO2 emission scenarios in the literature with the post-SRES scenarios [Figure 3.8]. Note: Two vertical bars on the right extend from the minimum to maximum of the distribution of scenarios and indicate the 5th, 25th, 50th, 75th and the 95th percentiles of the distributions by 2100.
GDP metrics For long-term scenarios, economic growth is usually reported in the form of growth in GDP or gross national product (GNP). To get a meaningful comparison of the real size of economic activities over time and between countries, GDP is reported in constant prices taken from a base year. The choice of the conversion factor, Market Exchange Rate (MER) or Purchasing Power Parity (PPP), depends on the type of analysis being undertaken. However, when it comes to calculating emissions (or other physical measures like energy), the choice between MER and PPP-based representations of GDP should not matter, since emission intensity will change (in a compensating manner) when the GDP numbers change. Thus, if a consistent set of metrics is employed, the choice of metric should not appreciably affect the final emission level. A number of new studies in the literature concur that the actual choice of exchange rates does not itself have an appreciable effect on long-term emission projections. In the case of SRES, the emissions trajectories are the same whether economic activities in the four scenario families are measured in MER or PPP. There are studies that find some differences in emission levels between PPP and MER-based estimates. These results depend critically on convergence assumptions, among other things. In some of the short-term scenarios (with a horizon to 2030) a bottom-up approach is taken where assumptions about productivity growth and investment/saving decisions are the main drivers of growth in the models. In long-term scenarios, a top-down approach is more commonly used where the actual growth rates are more directly prescribed on the basis of convergence or other assumptions about long-term growth potentials. Different results can also be due to inconsistencies in adjusting the metrics of energy efficiency improvement when moving from MER to PPP-based calculations.
38
Evidence from the limited number of new PPP-based studies indicates that the choice of metric for GDP (MER or PPP) does not appreciably affect the projected emissions, when the metrics are used consistently. The differences, if any, are small compared with the uncertainties caused by assumptions on other parameters, for example, technological change. The debate clearly shows, however, the need for modellers to be more transparent in explaining conversion factors as well as taking care in making assumptions on exogenous factors (high agreement, much evidence) [3.2.1]. Stabilization scenarios A commonly used target in the literature is stabilization of CO2 concentrations in the atmosphere. If more than one GHG is studied, a useful alternative is to formulate a GHG-concentration target in terms of CO2-equivalent concentration or radiative forcing, thereby weighting the concentrations of the different gases by their radiative properties. Another option is to stabilize or target global mean temperature. The advantage of radiativeforcing targets over temperature targets is that the calculation of radiative forcing does not depend on climate sensitivity. The disadvantage is that a wide range of temperature impacts is possible for each radiative-forcing level. Temperature targets, on the other hand, have the important advantage of being more directly linked to climate change impacts. Another approach is to calculate the risks or the probability of exceeding particular values of global annual mean temperature rise since pre-industrial times for specific stabilization or radiativeforcing targets. There is a clear and strong correlation between the CO2-equivalent concentrations (or radiative forcing) and the CO2-only concentrations by 2100 in the published studies, because CO2 is the most important contributor to radiative forcing. Based on this relationship, to facilitate scenario comparison and assessment, stabilization scenarios (both multi-gas and CO2only studies) have been grouped into different categories that vary in the stringency of the targets (Table TS.2). Essentially, any specific concentration or radiative-forcing target requires emissions to fall to very low levels as the removal processes of the ocean and terrestrial systems saturate. Higher stabilization targets do push back the timing of this ultimate result beyond 2100. However, to reach a given stabilization target, emissions must ultimately be reduced well below current levels. For achievement of the stabilization categories I and II, negative net emissions are required towards the end of the century in many scenarios considered (Figure TS. 8) (high agreement, much evidence) [3.3.5]. The timing of emission reductions depends on the stringency of the stabilization target. Stringent targets require an earlier peak in CO2 emissions (see Figure TS.8). In the majority of the scenarios in the most stringent stabilization category (I), emissions are required to decline before 2015 and be further reduced to less
Technical Summary
Table TS.2: Classification of recent (Post-Third Assessment Report) stabilization scenarios according to different stabilization targets and alternative stabilization metrics [Table 3.5].
Category
Additional radiative forcing (W/m2)
CO2 concentration (ppm)
CO2-eq concentration (ppm)
Global mean temperature increase above pre-industrial at equilibrium, using “best estimate” climate sensitivitya), b) (ºC)
Peaking year for CO2 emissionsc)
Change in global CO2 emissions in 2050 (% of 2000 emissions)c)
No. of assessed scenarios
I
2.5-3.0
350-400
445-490
2.0-2.4
2000 - 2015
-85 to -50
6
II
3.0-3.5
400-440
490-535
2.4-2.8
2000 - 2020
-60 to -30
18
III
3.5-4.0
440-485
535-590
2.8-3.2
2010 - 2030
-30 to +5
21
IV
4.0-5.0
485-570
590-710
3.2-4.0
2020 - 2060
+10 to +60
118
V
5.0-6.0
570-660
710-855
4.0-4.9
2050 - 2080
+25 to +85
9
VI
6.0-7.5
660-790
855-1130
4.9-6.1
2060 - 2090
+90 to +140
5 Total
177
Notes: a) Note that global mean temperature at equilibrium is different from expected global mean temperatures in 2100 due to the inertia of the climate system. b) The simple relationships Teq = T2×CO2 × ln([CO2]/278)/ln(2) and ∆Q = 5.35 × ln ([CO2]/278) are used. Non-linearities in the feedbacks (including e.g., ice cover and carbon cycle) may cause time dependence of the effective climate sensitivity, as well as leading to larger uncertainties for greater warming levels. The best-estimate climate sensitivity (3 ºC) refers to the most likely value, that is, the mode of the climate sensitivity PDF consistent with the WGI assessment of climate sensitivity and drawn from additional consideration of Box 10.2, Figure 2, in the WGI AR4. c) Ranges correspond to the 15th to 85th percentile of the Post-Third Assessment Report (TAR) scenario distribution. CO2emissions are shown, so multi-gas scenarios can be compared with CO2-only scenarios. Note that the classification needs to be used with care. Each category includes a range of studies going from the upper to the lower boundary. The classification of studies was done on the basis of the reported targets (thus including modelling uncertainties). In addition, the relationship that was used to relate different stabilization metrics is also subject to uncertainty (see Figure 3.16).
90 75 60
GtCO2/year
Category I
90
350 - 400 ppm CO2 445 - 490 ppm CO2 eq. n = 6 Scenarios peaking year 2000-2015
75 60
45
45
30
30
15
15
0
0
-15
-15
-30 2000
90 75 60
2020
GtCO2/year
2040
2060
2080
2100
90
45
30
30
15
15
0
0
-15
-15
90
GtCO2/year
2040
2060
2080
2100
Category V 650 ppm CO2 TAR Range
75
90 60 45
30
30
15
15 0
570 - 660 ppm CO2 710 - 855 ppm CO2 eq. n = 9 Scenarios peaking year 2050-2080
-30 2000
2020
-15 2040
2080
2100
2060
2080
550 ppm CO2 TAR Range
2100
485 - 570 ppm CO2 590 - 710 ppm CO2 eq. n = 118 Scenarios peaking year 2020-2060
2020
2040
2060
2080
2100
Category VI
GtCO2/year
75
45
0
2060
Category IV
GtCO2/year
-30 2000
60
-15
2040
60
45
2020
2020
75 450 ppm CO2 TAR Range
-30 2000
400 - 440 ppm CO2 490 - 535 ppm CO2 eq. n = 18 Scenarios peaking year 2000-2020
-30 2000
Category III
440 - 485 ppm CO2 535 - 590 ppm CO2 eq. n = 21 Scenarios peaking year 2010-2030
Category II
GtCO2/year
750 ppm CO2 TAR Range 660 - 790 ppm CO2 855 - 1130 ppm CO2 eq. n = 5 Scenarios peaking year 2060-2090
-30 2000
2020
2040
2060
2080
2100
Figure TS.8: Emission pathways of mitigation scenarios for alternative categories of stabilization targets (Category I to VI as defined in the box in each panel). Lightbrown shaded areas give the CO2 emissions for the recent mitigation scenarios developed post-TAR. Green shaded and hatched areas depict the range of more than 80 TAR stabilization scenarios (Morita et al., 2001). Category I and II scenarios explore stabilization targets below the lowest of TAR. Base year emissions may differ between models due to differences in sector and industry coverage. To reach the lower stabilization levels some scenarios deploy removal of CO2 from the atmosphere (negative emissions) using technologies such as biomass energy production utilizing carbon capture and storage [Figure 3.17].
39
Technical Summary
2030
2050
stabilization level ppm CO2-eq 500
2100
stabilization level ppm CO2-eq 700
800
900
1000
1100
GDP losses, %
600
500
stabilization level ppm CO2-eq
600
700
800
900
1000
1100
500
10
10
8
8
6
6
4
4
2
2
0 2.5
0 2.5
IGSM-CCSP
600
700
800
900
1000
1100
MERGE-CCSP MiniCAM-CCSP MESSAGE-A2 ASF-A2 PS AIM-A1-PS MiniCAM-A1 WorldScan-A1 DEMETER-IMCP ENTICE-IMCP MIND-IMCP
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
W/m2 III
IV
V
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
W/m2
-2
II
I
3.0
VI
I
category
III
IV
V
IV
I
category
ppm CO2-eq 500
700
800
900
1000 1100
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
MESSAGE-B2 WorldScan-B2-PS
II
III
IV
V
MESSAGE-B1
VI
category
ppm CO2-eq 600
3.5
W/m2
-2
II
RICE FAST-IMCP 3.0
500
ppm CO2-eq 600
700
800
900
1000 1100
500
500
500
500
400
400
400
300
300
300
200
200
200
100
100
100
IGSM-CCSP 600
700
800
900
1000 1100
MERGE-CCSP
Carbon price, US$/tCO2
MiniCAM-CCSP MESSAGE-A2 IMAGE-A1 DEMETER-IMCP ENTICE-IMCP MIND-IMCP RICE FAST-IMCP GET-LFL-IMCP MESSAGE-B2 IMAGE-B2 0 2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
W/m2
7.5
0 2.5
4.0
3.5
3.0
4.5
5.0
5.5
6.0
6.5
7.0
W/m2
7.5
0 2.5
4.0
3.5
3.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
IMAGE-B2-BECS MESSAGE-B1
W/m2
IMAGE-B1 I
II
category
III
IV
V
VI
I
II
III
IV
V
category
VI
I
II
III
IV
V
VI
category
Figure TS.9: Relationship between the cost of mitigation and long-term stabilization targets (radiative forcing compared with pre-industrial level, W/m2 and CO2-eq concentrations) [Figure 3.25]. Notes: Panels give costs measured as percentage loss of GDP (top), and carbon price (bottom). Left-hand panels for 2030, middle panels for 2050 and right-hand panels for 2100. Individual coloured lines denote selected studies with representative cost dynamics from very high to very low cost estimates. Scenarios from models sharing similar baseline assumptions are shown in the same colour. The grey shaded range represents the 80th percentile of TAR and post-TAR scenarios. Solid lines show representative scenarios considering all radiatively active gases. Dashed lines represent multi-gas scenarios where the target is defined by the six Kyoto gases (other multi-gas scenarios consider all radiatively active gases). CO2 stabilization scenarios are added based on the relationship between CO2 concentration and the radiativeforcing targets given in Figure 3.16.
than 50% of today’s emissions by 2050. For category III, global emissions in the scenarios generally peak around 2010–2030, followed by a return to 2000 levels on average around 2040. For category IV, the median emissions peak around 2040 (Figure TS.9) (high agreement, much evidence). The costs of stabilization depend on the stabilization target and level, the baseline and the portfolio of technologies considered, as well as the rate of technological change. Global mitigation costs9 rise with lower stabilization levels and with higher baseline emissions. Costs in 2050 for multi-gas stabilization at 650 ppm CO2-eq (cat IV) are between a 2% loss or a one procent increase10 of GDP in 2050. For 550 ppm CO2-eq (cat III) these costs are a range of a very small increase to 4% loss of GDP11. For stabilization levels between 445 and 535 ppm CO2-eq. costs are lower than 5.5% loss of GDP, but the number of studies is limited and they generally use low baselines.
9
A multi-gas approach and inclusion of carbon sinks generally reduces costs substantially compared with CO2 emission abatement only. Global average costs of stabilization are uncertain, because assumptions on baselines and mitigation options in models vary a lot and have a major impact. For some countries, sectors or shorter time periods, costs could vary considerably from the global and long-term average (high agreement, much evidence) [3.3.5]. Recent stabilization studies have found that land-use mitigation options (both non-CO2 and CO2) provide costeffective abatement flexibility in achieving 2100 stabilization targets. In some scenarios, increased commercial biomass energy (solid and liquid fuel) is significant in stabilization, providing 5–30% of cumulative abatement and potentially 10– 25% of total primary energy over the century, especially as a net negative emissions strategy that combines biomass energy with CO2 capture and storage.
Studies on mitigation portfolios and macro-economic costs assessed in this report are based on a global least-cost approach, with optimal mitigation portfolios and without allocation of emission allowances to regions. If regions are excluded or non-optimal portfolios are chosen, global costs will go up. The variation in mitigation portfolios and their costs for a given stabilization level is caused by different assumptions, such as on baselines (lower baselines give lower costs), GHGs and mitigation options considered (more gases and mitigation options give lower costs), cost curves for mitigation options and rate of technological change. 10 The median and the 10th–90th percentile range of the analysed data are given. 11 Loss of GDP of 4% in 2050 is equivalent to a reduction of the annual GDP growth rate of about 0.1 percentage points.
40
Technical Summary
deployment of technologies leads to benefits of learning and cost reductions (high agreement, much evidence) [3.4].
The baseline choice is crucial in determining the nature and cost of stabilization. This influence is due mainly to different assumptions about technological change in the baseline scenarios.
The different scenario categories also reflect different contributions of mitigation measures. However, all stabilization scenarios concur that 60–80% of all reductions would come from the energy and industry sectors. Non-CO2 gases and landuse would contribute the remaining 30–40% (see for illustrative examples Figure TS. 10). New studies exploring more stringent stabilization levels indicate that a wider portfolio of technologies is needed. Those could include nuclear, carbon capture and storage (CCS) and bioenergy with carbon capture and geologic storage (BECS) (high agreement, much evidence) [3.3.5].
The role of technologies Virtually all scenarios assume that technological and structural changes occur during this century, leading to relative reduction of emissions compared with the hypothetical case of attempting to ‘keep’ the emission intensities of GDP and economic structures the same as today (see Chapter 2, Section 2.9.1.3]. Baseline scenarios usually assume significant technological change and diffusion of new and advanced technologies. In mitigation scenarios there is additional technological change ‘induced’ through various policies and measures. Long-term stabilization scenarios highlight the importance of technology improvements, advanced technologies, learning by doing and endogenous technology change both for achieving the stabilization targets and for cost reduction. While the technology improvement and use of advanced technologies have been introduced in scenarios largely exogenously in most of the literature, new literature covers learning-by-doing and endogenous technological change. These newer scenarios show higher benefits of early action, as models assume that early
Mitigation and adaptation in the light of climate change impacts and decision-making under uncertainties Concern about key vulnerabilities and notions of what is dangerous climate change will affect decisions about long-term climate change objectives and hence mitigation pathways. Key vulnerabilities traverse different human and natural systems and exist at different levels of temperature change. More stringent stabilization scenarios achieve more stringent climate targets and lower the risk of triggering key vulnerabilities related to climate change. Using the ‘best estimate’ of climate sensitivity12,
2000 - 2030
2000 - 2100
Energy conservation & efficiency emissions reductions for 650 ppm
Fossil fuel switch
additional reductions for 490-540 ppm
Renewables Nuclear CCS IMAGE MESSAGE
Forest sinks
AIM IPAC
Non-CO2 0 20 40 60 80 100 120 Cumulative emission reduction GtCO2-eq
0
120
500
1000 1500 Cumulative emission reduction GtCO2-eq
N/A
2000
Figure TS.10: Cumulative emission reductions for alternative mitigation measures for 2000–2030 (left-hand panel) and for 2000–2100 (right-hand panel). The figure shows illustrative scenarios from four models (AIM, IMAGE, IPAC and MESSAGE) aiming at the stabilization at low (490–540 ppm CO2-eq) and intermediate levels (650 ppm CO2-eq) respectively. Dark bars denote reductions for a target of 650 ppm CO2-eq and light bars the additional reductions to achieve 490–540 ppm CO2-eq. Note that some models do not consider mitigation through forest sink enhancement (AIM and IPAC) or CCS (AIM) and that the share of low-carbon energy options in total energy supply is also determined by inclusion of these options in the baseline. CCS includes carbon capture and storage from biomass. Forest sinks include reducing emissions from deforestation [Figure 3.23].
12
The equilibrium climate sensitivity is a measure of the climate system response to sustained radiative forcing. It is not a projection but is defined as the global average surface warming following a doubling of carbon dioxide concentrations [AR4 WGI SPM].
41
Technical Summary
Equilibrium global mean temperature increase above pre-industrial (°C) 10 8 VI
6
V IV
4 I
II
III
2 0 300
400 500 600 700 800 GHG concentration stabilization level (ppm CO2 eq)
900
1000
Figure TS.11: Stabilization scenario categories as reported in Figure TS.8 (coloured bands) and their relationship to equilibrium global mean temperature change above pre-industrial temperatures [Figure 3.38]. Notes: Middle (black) line – ‘best estimate’ climate sensitivity of 3°C; upper (red) line – upper bound of likely range of climate sensitivity of 4.5°C; lower (blue) line – lower bound of likely range of climate sensitivity of 2°C. Coloured shading shows the concentration bands for stabilization of GHGs in the atmosphere corresponding to the stabilization scenario categories I to VI as indicated in Table TS.2.
the most stringent scenarios (stabilizing at 445–490 ppm CO2eq) could limit global mean temperature increases to 2-2.4°C above pre-industrial, at equilibrium, requiring emissions to peak within 10 years and to be around 50% of current levels by 2050. Scenarios stabilizing at 535-590 ppm CO2-eq could limit the increase to 2.8-3.2°C above pre-industrial and those at 590710 CO2-eq to 3.2-4°C, requiring emissions to peak within the next 25 and 55 years respectively (see Figure TS.11) [3.3, 3.5]. The risk of higher climate sensitivities increases the probability of exceeding any threshold for specific key vulnerabilities. Emission scenarios that lead to temporary overshooting of concentration ceilings can lead to higher rates of climate change over the century and increase the probability of exceeding key vulnerability thresholds. Results from studies exploring the effect of carbon cycle and climate feedbacks indicate that the above-mentioned concentration levels and the associated warming of a given emissions scenario might be an underestimate. With higher climate sensitivity, earlier and more stringent mitigation measures are necessary to reach the same concentration level. Decision-making about the appropriate level of mitigation is an iterative risk-management process considering investment in mitigation and adaptation, co-benefits of undertaking climate change decisions and the damages due to climate change. It is intertwined with decisions on sustainability, equity and development pathways. Cost-benefit analysis, as one of the available tools, tries to quantify climate change damage in monetary terms (as social cost of carbon (SCC) or timediscounted damage). Due to large uncertainties and difficulties in quantifying non-market damage, it is still difficult to estimate SCC with confidence. Results depend on a large number of 42
normative and empirical assumptions that are not known with any certainty. Limited and early analytical results from integrated analyses of the costs and benefits of mitigation indicate that these are broadly comparable in magnitude, but do not as yet permit an unambiguous determination of an emissions pathway or stabilization level where benefits exceed costs. Integrated assessment of the economic costs and benefits of different mitigation pathways shows that the economically optimal timing and level of mitigation depends upon the uncertain shape and character of the assumed climate change damage cost curve. To illustrate this dependency: • if the climate change damage cost curve grows slowly and regularly, and there is good foresight (which increases the potential for timely adaptation), later and less stringent mitigation is economically justified; • alternatively if the damage cost curve increases steeply, or contains non-linearities (e.g. vulnerability thresholds or even small probabilities of catastrophic events), earlier and more stringent mitigation is economically justified (high agreement, much evidence) [3.6.1]. Linkages between short term and long term For any chosen GHG-stabilization target, near-term decisions can be made regarding mitigation opportunities to help maintain a consistent emissions trajectory within a range of long-term stabilization targets. Economy-wide modelling of long-term global stabilization targets can help inform near-term mitigation choices. A compilation of results from short-and long-term models using scenarios with stabilization targets in the 3–5 W/m2 range (category II to III), reveals that in 2030, for carbon prices of less than 20 US$/tCO2-eq, emission reductions of in the
Technical Summary
range of 9-18 GtCO2-eq/yr across all GHGs can be expected. For carbon prices less than 50 US$/tCO2-eq this range is 14–23 GtCO2-eq/yr and for carbon prices less than US$100/tCO2-eq it is 17-26 GtCO2-eq/yr. (high agreement, much evidence).
4000
Mtoe
3500 3000
Three important considerations need to be remembered with regard to the reported marginal costs. First, these mitigation scenarios assume complete ‘what’ and ‘where’ flexibility; that is, there is full substitution among GHGs, and reductions take place anywhere in the world as soon as the models begin their analyses. Second, the marginal costs of realizing these levels of mitigation increase in the time horizon beyond 2030. Third, at the economic-sector level, emission-reduction potential for all GHGs varies significantly across the different model scenarios (high agreement, much evidence) [3.6.2].
2500 2000 1500 1000 500 0
A risk management or ‘hedging’ approach can assist policymakers to advance mitigation decisions in the absence of a longterm target and in the face of large uncertainties related to the cost of mitigation, the efficacy of adaptation and the negative impacts of climate change. The extent and the timing of the desirable hedging strategy will depend on the stakes, the odds and societies’ attitudes to risks, for example, with respect to risks of abrupt change in geophysical systems and other key vulnerabilities. A variety of integrated assessment approaches exist to assess mitigation benefits in the context of policy decisions related to such long-term climate goals. There will be ample opportunity for learning and mid-course corrections as new information becomes available. However, actions in the short term will largely determine long-term global mean temperatures and thus what corresponding climate change impacts can be avoided. Delayed emission reductions lead to investments that lock in more emission-intensive infrastructure and development pathways. This significantly constrains the opportunities to achieve lower stabilization levels and increases the risk of more severe climate change impacts. Hence, analysis of near-term decisions should not be decoupled from analysis that considers long-term climate change outcomes (high agreement, much evidence) [3.6; 3.5.2].
Asia
Note: EECCA = countries of Eastern Europe, the Caucasus and Central Asia. 1000 Mtoe = 42 EJ.
compromise energy access, equity and sustainable development of the poorest countries and interfere with reaching povertyreduction targets that, in turn, imply improved access to electricity, modern cooking and heating fuels and transportation (high agreement, much evidence) [4.2.4]. Total fossil fuel consumption has increased steadily during the past three decades. Consumption of nuclear energy has continued to grow, though at a slower rate than in the 1980s. Large hydro and geothermal energy are relatively static. Between 1970 and 2004, the share of fossil fuels dropped from 86% to 81%. Wind and solar are growing most rapidly, but from a very low base (Figure TS.13) (high agreement, much evidence) [4.2]. Mtoe
Energy supply
Other renewables Hydro Nuclear Biomass
12000
Status of the sector and development until 2030
10000
Global energy demand continues to grow, but with regional differences. The annual average growth of global primary energy consumption was 1.4 % per year in the 1990–2004 period. This was lower than in the previous two decades due to the economic transition in Eastern Europe, the Caucasus and Central Asia, but energy consumption in that region is now moving upwards again (Figure TS.12) (high agreement, much evidence) [4.2.1].
8000
Rapid growth in energy consumption per capita is occurring in many developing countries. Africa is the region with the lowest per capita consumption. Increasing prices of oil and gas
Africa
Figure TS.12: Annual primary energy consumption, including traditional biomass, 1971 to 2003 [Figure 4.2].
14000
4
North Latin Europe EECCA Middle America America East
Gas
6000
Coal
4000 2000 0 1971
Oil 1980
1990
2000
2005
Figure TS.13: World primary energy consumption by fuel type. [Figure 4.5].
43
Technical Summary
Most business-as-usual (BAU) scenarios point to continued growth of world population (although at lower rates than predicted decades ago) and GDP, leading to a significant growth in energy demand. High energy-demand growth rates in Asia (3.2% per year 1990–2004) are projected to continue and to be met mainly by fossil fuels (high agreement, much evidence) [4.2]. Absolute fossil fuel scarcity at the global level is not a significant factor in considering climate change mitigation. Conventional oil production will eventually peak, but it is uncertain exactly when and what the repercussions will be. The energy in conventional natural gas is more abundant than in conventional oil but, like oil, is not distributed evenly around the globe. In the future, lack of security of oil and gas supplies for consuming nations may drive a shift to coal, nuclear power and/or renewable energy. There is also a trend towards more efficient and convenient energy carriers (electricity, and liquid and gaseous fuels) instead of solids (high agreement, much evidence) [4.3.1]. In all regions of the world, emphasis on security of supply has grown since the Third Assessment Report (TAR). This is coupled with reduced investments in infrastructure, increased global demand, political instability in key areas and the threats of conflict, terrorism and extreme weather events. New energy infrastructure investments in developing countries and upgrades of capacity in developed countries opens a window of opportunity for exploiting the co-benefits of choices in the energy mix in order to lower GHG emissions from what they otherwise would be (high agreement, much evidence) [4.2.4; 4.1]. The conundrum for many governments has become how best to meet the ever growing demand for reliable energy services while limiting the economic costs to their constituents, ensuring energy security, reducing dependence on imported energy sources and minimizing emissions of the associated GHGs and other pollutants. Selection of energy-supply systems for each region of the world will depend on their development, existing infrastructure and the local comparative costs of the available energy resources (high agreement, much evidence) [4.1]. If fossil fuel prices remain high, demand may decrease temporarily until other hydrocarbon reserves in the form of oil sands, oil shales, coal-to-liquids, gas-to-liquids etc. become commercially viable. Should this happen, emissions will increase further as the carbon intensity increases, unless carbon dioxide capture and storage (CCS) is applied. Due to increased energy security concerns and recent increases in gas prices, there is growing interest in new, more efficient, coal-based power plants. A critical issue for future GHG emissions is how quickly new coal plants are going to be equipped with CCS technology, which will increase the costs of electricity. Whether building ‘capture ready’ plants is more cost-effective than retrofitting plants or building a new plant integrated with CCS 44
depends on economic and technical assumptions. Continuing high fossil fuel prices may also trigger more nuclear and/or renewable energy, although price volatility will be a disincentive for investors. Concerns about safety, weapons proliferation and waste remain as constraints for nuclear power. Hydrogen may also eventually contribute as an energy carrier with low carbon emissions, dependent on the source of the hydrogen and the successful uptake of CCS for hydrogen production from coal or gas. Renewable energy must either be used in a distributed manner or will need to be concentrated to meet the intensive energy demands of cities and industries, because, unlike fossil fuel sources, the sources of renewable energy are widely distributed with low energy returns per exploited area (medium agreement, medium evidence) [4.3]. If energy demand continues to grow along the current trajectory, an improved infrastructure and conversion system will, by 2030, require a total cumulative investment of over US$2005 20 trillion (20 x 1012). For comparison, the total capital investment by the global energy industry is currently around 300 billion US$ per year (300 x 109) (medium agreement, medium evidence) [4.1]. Global and regional emission trends With the exception of the countries in Eastern Europe, the Caucasus and Central Asia (where emissions declined post-1990 but are now rising again) and Europe (currently stable), carbon emissions have continued to rise. Business-as-usual emissions to 2030 will increase significantly. Without effective policy actions, global CO2 emissions from fossil fuel combustion are predicted to rise at a minimum of more than 40%, from around 25 GtCO2-eq/yr (6.6 GtC-eq) in 2000 to 37-53 GtCO2-eq/yr (10-14 GtC-eq) by 2030 [4.2.3]. In 2004, emissions from power generation and heat supply alone were 12.7 GtCO2-eq (26% of total emissions) including 2.2 GtCO2eq from CH4. In 2030, according to the World Energy Outlook 2006 baseline, these will have increased to 17.7 GtCO2-eq. (high agreement, much evidence) [4.2.2]. Description and assessment of mitigation technologies and practices, options, potentials and costs in the electricity generation sector The electricity sector has a significant mitigation potential using a range of technologies (Table TS.3). The economic potential for mitigation of each individual technology is based on what might be a realistic deployment expectation of the various technologies using all efforts, but given practical constraints on rate of uptake, public acceptance, capacity building and commercialization. Competition between options and the influence of end-use energy conservation and efficiency improvement is not included [4.4]. A wide range of energy-supply mitigation options are available and cost effective at carbon prices of <20US$/tCO2
Technical Summary
Table TS.3: Potential GHG emissions avoided by 2030 for selected electricity generation mitigation technologies (in excess of the IEA World Energy Outlook (2004) Reference baseline) employed in isolation with estimated mitigation potential shares spread across each cost range (2006 US$/tCO2-eq) [Table 4.19].
Regional groupings Fuel switch and plant efficiency
OECDa
Mitigation potential; total emissions saved in 2030 (GtCO2-eq)
Mitigation potential (%) for specific carbon price ranges (US$/tCO2-eq avoided) <0
0-20
20-50
EITb Non-OECD World
0.39 0.04 0.64 1.07
Nuclear
OECD EIT Non-OECD World
0.93 0.23 0.72 1.88
50 50 50
50 50 50
Hydro
OECD EIT Non-OECD World
0.39 0.00 0.48 0.87
85
15
25
35
40
Wind
OECD EIT Non-OECD World
0.45 0.06 0.42 0.93
35 35 35
40 45 50
25 20 15
Bio-energy
OECD EIT Non-OECD World
0.20 0.07 0.95 1.22
20 20 20
25 25 30
40 40 45
Geothermal
OECD EIT Non-OECD World
0.09 0.03 0.31 0.43
35 35 35
40 45 50
25 20 15
Solar PV and concentrated solar power
OECD EIT Non-OECD World
0.03 0.01 0.21 0.25
CCS + coal
OECD EIT Non-OECD World
0.28 0.01 0.20 0.49
CCS + gas
OECD EIT Non-OECD World
0.09 0.04 0.09 0.22
50-100
>100
100 100 100
15 15 5
20 20 25
80 80 75
100 100 100
30
100 70 100
Notes: a) Organization for Economic Cooperation and Development b) Economies in Transition
including fuel switching and power-plant efficiency improvements, nuclear power and renewable energy systems. CCS will become cost effective at higher carbon prices. Other options still under development include advanced nuclear power, advanced renewables, second-generation biofuels and, in the longer term, the possible use of hydrogen as an energy carrier (high agreement, much evidence) [4.3, 4.4]. Since the estimates in Table TS.3 are for the mitigation potentials of individual options without considering the actual supply mix, they cannot be added. An additional analysis of the supply mix to avoid double counting was therefore carried out.
For this analysis, it was assumed that the capacity of thermal electricity generation capacity would be substituted gradually and new power plants would be built to comply with demand, under the following conditions: 1) Switching from coal to gas was assumed for 20% of the coal plants, as this is the cheapest option. 2) The replacement of existing fossil fuel plants and the building of new plants up to 2030 to meet increasing power demand was shared between efficient fossil fuel plants, renewables, nuclear and coal and gas-fired plants with CCS. No early retirement of plants or stranded assets was assumed. 3) Low- or zero-carbon technologies are employed proportional 45
Technical Summary
Table TS.4: Projected power demand increase from 2010 to 2030 as met by new, more efficient additional and replacement plants and the resulting mitigation potential above the World Energy Outlook 2004 baseline [Table 4.20].
Power plant efficiencies by 2030 (based on IEA 2004a)a (%) OECD Coal Oil Gas Nuclear Hydro Biomass Other renew CCS
41 40 48 33 100 28 63
Economies In Transition (EIT) Coal Oil Gas Nuclear Hydro Biomass Other renew CCS
Total
Generation from additional new plant by 2030 (TWh)
11,302
2942
4521
4079 472 2374 2462 1402 237 276
657 –163C 1771 –325 127 168 707
1632 189 950 985 561 95 110
1746
722
698
32 29 39 33 100 48 36
381 69 652 292 338 4 10
13 –8 672 –20 35 7 23
152 28 261 117 135 2 4
7137
7807
38 38 46 33 100 19 28
3232 646 1401 231 1472 85 70
3729 166 2459 289 874 126 164
20185
11471
Non-OECD/ EIT Coal Oil Gas Nuclear Hydro Biomass Other renew CCS
Existing mix of power generation in 2010 ( TWh)
Generation from new plant replacing old, existing 2010 plant by 2030 (TWh)
Share of mix of generation of total new and replacement plant built by 2030 including CCS at various carbon prices (US$/tCO2-eq)b <20 US$/ TWh
<50 US$/ TWh
<100 US$/ TWh
7463 899 13 1793 2084 1295 263 1116 0
121 2 637 2084 1295 499 1544 1282
2855 1293 258 560 92 589 34 28
1697 179 2279 1356 2106 1294 1154 598 19545
<50 US$/t
<100 US$/t
1.58
2.58
2.66
0.32
0.42
0.49
2.06
3.44
4.08
3.95
6.44
7.22
29 4 240 442 170 121 191 222
10662 2807 297 3114 1356 1463 621 1004 0
8074
46 7 357 442 170 109 167 123
<20 US$/t
0 0 458 1777 1111 509 1526 2082
1420 72 11 537 442 170 47 142 0
Total GtCO2-eq avoided by fuel switching, CCS and displacing some fossil fuel generation with low-carbon options of wind, solar, geothermal, hydro, nuclear and biomass
1133 120 1856 1356 2106 1443 1303 1345
Notes: a) Implied efficiencies calculated from WEO 2004 (IEA, 2004b) = Power output (EJ)/Estimated power input (EJ). See Appendix 1, Chapter 11. b) At higher carbon prices, more coal, oil and gas power generation is displaced by low- and zero-carbon options. Since nuclear and hydro are cost competitive at <20US$/tCO2-eq in most regions (Chapter 4, Table 4.4.4), their share remains constant. c) Negative data depicts a decline in generation, which was included in the analysis.
to their estimated maximum shares in electricity generation in 2030. These shares are based on the literature, taking into account resource availability, relative costs and variability of supply related to intermittency issues in the power grid, and were differentiated according to carbon cost levels. The resulting economic mitigation potential for the energy-supply sector by 2030 from improved thermal powerplant efficiency, fuel switching and the implementation of more nuclear, renewables, fuel switching and CCS to meet growing demand is around 7.2 GtCO2-eq at carbon prices <100 US$/tCO2-eq. At costs <20 US$/tCO2-eq the reduction potential is estimated at 3.9 GtCO2-eq (Table TS.4). At this carbon price level, the share of renewable energy in electricity 46
generation would increase from 20% in 2010 to about 30% in 2030. At carbon prices <50 US$/tCO2-eq, the share would increase to 35% of total electricity generation. The share of nuclear energy would be about 18% in 2030 at carbon prices <50 US$/tCO2-eq, and would not change much at higher prices as other technologies would be competitive. For assessment of the economic potential, maximum technical shares for the employment of low- or zero-carbon technologies were assumed and the estimate is therefore at the high end of the wide range found in the literature. If, for instance, only 70% of the assumed shares is reached, the mitigation potential at carbon prices <100 US$/tCO2-eq would be almost halved. Potential savings in electricity demand in end-use sectors reduce the need for mitigation measures in the
Technical Summary
power sector. When the impact of mitigation measures in the building and industry sectors on electricity demand (outlined in Chapter 11) is taken into account, a lower mitigation potential for the energy-supply sector results than the stand-alone figure reported here (medium agreement, limited evidence) [4.4]. Interactions of mitigation options with vulnerability and adaptation Many energy systems are themselves vulnerable to climate change. Fossil fuel based offshore and coastal oil and gas extraction systems are vulnerable to extreme weather events. Cooling of conventional and nuclear power plants may become problematic if river waters are warmer. Renewable energy resources can also be affected adversely by climate change (such as solar systems impacted by changes in cloud cover; hydropower generation influenced by changes in river discharge, glaciers and snow melt; windpower influenced by changing wind velocity; and energy crop yields reduced by drought and higher temperatures). Some adaptation measures to climate change, like air-conditioning and water pumps use energy and may contribute to even higher CO2 emissions, and thus necessitate even more mitigation (high agreement, limited evidence) [4.5.5]. Effectiveness of and experience with climate policies, potentials, barriers, opportunities and implementation issues The need for immediate short-term action in order to make any significant impact in the longer term has become apparent, as has the need to apply the whole spectrum of policy instruments, since no single instrument will enable a large-scale transition in energy-supply systems on a global basis. Large-scale energy conversion technologies have a life of several decades and hence a turnover of only 1–3% per year. That means that policy decisions taken today will affect the rate of deployment of carbon-emitting technologies for several decades. They will have profound consequences on development paths, especially in a rapidly developing world [4.1]. Economic and regulatory instruments have been employed. Approaches to encourage the greater uptake of low-carbon energy-supply systems include reducing fossil fuel subsidies and stimulating front-runners in specific technologies through active government involvement in market creation (such as in Denmark for wind energy and Japan with solar photovoltaic (PV)). Reducing fossil fuel subsidies has been difficult, as it meets resistance by vested interests. In terms of support for renewable-electricity projects, feed-in-tariffs have been more effective than green certificate trading systems based on quotas. However, with increasing shares of renewables in the power mix, the adjustment of such tariffs becomes an issue. Tradable permit systems and the use of the Kyoto flexible mechanisms are expected to contribute substantially to emission reductions (medium agreement, medium evidence) [4.5].
Integrated and non-climate policies and co-benefits of mitigation policies Co-benefits of GHG mitigation in the energy supply sector can be substantial. When applying cost-effective energyefficiency measures, there is an immediate economic benefit to consumers from lower energy costs. Other co-benefits in terms of energy supply security, technological innovation, air-pollution abatement and employment also typically result at the local scale. This is especially true for renewables which can reduce import dependency and in many cases minimize transmission losses and costs. Electricity, transport fuels and heat supplied by renewable energy are less prone to price fluctuations, but in many cases have higher costs. As renewable energy technologies can be more labour-intensive than conventional technologies per unit of energy output, more employment will result. High investment costs of new energy system infrastructures can, however, be a major barrier to their implementation. Developing countries that continue to experience high economic growth will require significant increases in energy services that are currently being met mainly by fossil fuels. Increasing access to modern energy services can have multiple benefits. Their use can help improve air quality, particularly in large urban areas, and lead to a decrease in GHG emissions. An estimated 2400 GW of new power plants plus the related infrastructure will need to be built in developing countries by 2030 to meet increased consumer demand, requiring an investment of around 5 trillion US$ (5 x 1012). If well directed, such large investments provide opportunities for sustainable development. The integration of development policies with GHG mitigation objectives can deliver the advantages mentioned above and contribute to development goals pertaining to employment, poverty and equity. Analysis of possible policies should take into account these co-benefits. However, it should be noted again that, in specific circumstances, pursuing airpollution abatement or energy security aims can lead to more energy use and related GHG emissions. Liberalization and privatization policies to develop free energy markets aim to provide greater competition and lower consumer prices but have not always been successful in this regard, often resulting in a lack of capital investment and scant regard for environmental impacts (high agreement, much evidence) [4.2.4; 4.5.2; 4.5.3; 4.5.4]. Technology research, development, diffusion and transfer Investment in energy technology R&D has declined overall since the levels achieved in the late 1970s that resulted from the oil crisis. Between 1980 and 2002, public energy-related R&D investment declined by 50% in real terms. Current levels have risen, but may still be inadequate to develop the technologies needed to reduce GHG emissions and meet growing energy demand. Greater public and private investment will be required 47
Technical Summary
for rapid deployment of low-carbon energy technologies. Improved energy conversion technologies, energy transport and storage methods, load management, co-generation and community-based services will have to be developed (high agreement, limited evidence) [4.5.6]. Long-term outlook Outlooks from both the IEA and World Energy Council project increases in primary energy demand of between 40 and 150% by 2050 over today’s demand, depending on the scenarios for population and economic growth and the rate of technology development. Electricity use is expected to grow by between 110 and 260%. Both organizations realize that business-as-usual scenarios are not sustainable. It is well accepted that even with good decisionmaking and co-operation between the public and private sectors, the necessary transition will take time and the sooner it is begun the lower the costs will be (high agreement, much evidence) [4.2.3].
5
Transport and its infrastructure
Status and development of the sector Transport activity is increasing around the world as economies grow. This is especially true in many areas of the
developing world where globalization is expanding trade flows, and rising personal incomes are amplifying demand for motorized mobility. Current transportation activity is mainly driven by internal combustion engines powered by petroleum fuels (95% of the 83 EJ of world transport energy use in 2004). As a consequence, petroleum use closely follows the growth in transportation activity. In 2004, transport energy amounted to 26% of total world energy use. In the developed world, transport energy use continues to increase at slightly more than 1% per year; passenger transport currently consumes 60–75% of total transport energy there. In developing countries, transport energy use is rising faster (3 to 5% per year) and is projected to grow from 31% in 2002 to 43% of world transport energy use by 2025 [5.2.1, 5.2.2]. Transport activity is expected to grow robustly over the next several decades. Unless there is a major shift away from current patterns of energy use, projections foresee a continued growth in world transportation energy use of 2% per year, with energy use and carbon emissions about 80% above 2002 levels by 2030 [5.2.2]. In developed economies, motor vehicle ownership approaches five to eight cars for every ten inhabitants (Figure TS.14). In the developing world, levels of vehicle ownership are much lower; non-motorized transport plays a significant role, and there is a greater reliance on two- and three-wheeled motorized vehicles and public transport. The motorization of transport in the developing world is, however, expected to grow rapidly in
Vehicle Ownership/ 1000 Persons 900 800 USA
700 600
New Zealand
500
Australia
France
Spain
Sweden
400 Czech 300 Poland 200
Italy
Canada Japan Switzerland Belgium Germany Netherlands
UK
Denmark
Portugal Greece
Hungary
Argentina Saudi Arabia Mexico KoreaAfrica Peru 100 South Brazil China Turkey 0 India Philippines Russia
0
Malaysia
5000
10000
15000
20000
GDP per Capita (US$) Figure TS.14: Vehicle ownership and income per capita as a time line per country [Figure 5.2]. Note: data are for 1900–2002, but the years plotted vary by country, depending on data availability.
48
25000
30000
35000
Technical Summary
the coming decades. As incomes grow and the value of travellers’ time increases, travellers are expected to choose faster modes of transport, shifting from non-motorized to automotive, to air and high-speed rail. Increasing speed has generally led to greater energy intensity and higher GHG emissions. In addition to GHG emissions, the motorization of transport has created congestion and air-pollution problems in large cities all around the world (high agreement, much evidence) [5.2.1; 5.2.2; 5.5.4].
15
Gt CO2
historical data (IEA)
estimated data (WBCSD)
10 Air Sea 5
Emission trends Road
In 2004, the contribution of transport to total energy-related GHG emissions was about 23%, with emissions of CO2 and N2O amounting to about 6.3-6.4 GtCO2-eq. Transport sector CO2 emissions (6.2 GtCO2-eq. in 2004) have increased by around 27% since 1990 and its growth rate is the highest among the enduser sectors. Road transport currently accounts for 74% of total transport CO2 emissions. The share of non-OECD countries is 36% now and will increase rapidly to 46% by 2030 if current trends continue (high agreement, medium evidence) [5.2.2]. The transport sector also contributes small amounts of CH4 and N2O emissions from fuel combustion and F-gases from vehicle air-conditioning. CH4 emissions are between 0.1–0.3% of total transport GHG emissions, N2O between 2.0 and 2.8% (all figures based on US, Japan and EU data only). Emissions of F gases (CFC-12 + HFC-134a + HCFC-22) worldwide in 2003 were 4.9% of total transport CO2 emissions (medium agreement, limited evidence) [5.2.1]. Estimates of CO2 emissions from global aviation increased by a factor of about 1.5, from 330 MtCO2/yr in 1990 to 480 MtCO2/ yr in 2000, and accounted for about 2% of total anthropogenic CO2 emissions. Aviation CO2 emissions are projected to continue to grow strongly. In the absence of additional measures, projected annual improvements in aircraft fuel efficiency of the order of 1–2% will be largely surpassed by traffic growth of around 5% each year, leading to a projected increase in emissions of 3–4% per year (high agreement, medium evidence). Moreover, the overall climate impact of aviation is much greater than the impact of CO2 alone. As well as emitting CO2, aircraft contribute to climate change through the emission of nitrogen oxides (NOx), which are particularly effective in forming the GHG ozone when emitted at cruise altitudes. Aircraft also trigger the formation of condensation trails, or contrails, which are suspected of enhancing the formation of cirrus clouds, which add to the overall global warming effect. These effects are estimated to be about two to four times greater than those of aviation’s CO2 alone, even without considering the potential impact of cirrus cloud enhancement. The environmental effectiveness of future mitigation policies for aviation will depend on the extent to which these non-CO2 effects are also addressed (high agreement, medium evidence) [5.2.1; 5.2.2].
0 1970
1980
1990
2000
2010
2020
2030
2040
2050
Figure TS.15: Historical and projected CO2 emissions from transport [Figure 5.4].
All of the projections discussed above assume that world oil supplies will be more than adequate to support the expected growth in transport activity. There is ongoing debate, however, about whether the world is nearing a peak in conventional oil production that would require a significant and rapid transition to alternative energy sources. There is no shortage of alternative energy sources, including oil sands and oil shales, coal-toliquids, biofuels, electricity and hydrogen. Among these alternatives, unconventional fossil carbon resources would produce the least expensive fuels most compatible with the existing transportation infrastructure. Unfortunately, tapping into these fossil resources to power transportation would increase upstream carbon emissions and greatly increase the input of carbon into the atmosphere [5.2.2; 5.3]. Description and assessment of mitigation technologies and practices, options, potentials and costs Transport is distinguished from other energy-using sectors by its predominant reliance on a single fossil resource and by the infeasibility of capturing carbon emissions from transport vehicles with any known technologies. It is also important to view GHG-emission reductions in conjunction with air pollution, congestion and energy security (oil import) problems. Solutions therefore have to try to optimize improvement of transportation problems as a whole, not just GHG emissions [5.5.4]. There have been significant developments in mitigation technologies since the Third Assessment Report (TAR), and significant research, development and demonstration programmes on hydrogen-powered fuel-cell vehicles have been launched around the globe. In addition, there are still many opportunities for improvement of conventional technologies. Biofuels continue to be important in certain markets and have 49
Technical Summary
much greater potential for the future. With regard to non-CO2 emissions, vehicle air-conditioning systems based on low GWP refrigerants have been developed [5.3]. Road traffic: efficient technologies and alternative fuels Since the TAR, the energy efficiency of road vehicles has improved by the market success of cleaner directed-injection turbocharged (TDI) diesels and the continued market penetration of many incremental efficiency technologies; hybrid vehicles have also played a role, though their market penetration is currently small. Further technological advances are expected for hybrid vehicles and TDI diesel engines. A combination of these with other technologies, including materials substitution, reduced aerodynamic drag, reduced rolling resistance, reduced engine friction and pumping losses, has the potential to approximately double the fuel economy of ‘new’ light-duty vehicles by 2030, thereby roughly halving carbon emissions per vehicle mile travelled (note that this is only for a new car and not the fleet average) (medium agreement, medium evidence) [5.3.1]. Biofuels have the potential to replace a substantial part, but not all, petroleum use by transport. A recent IEA report estimated that the share of biofuels could increase to about 10% by 2030 at costs of 25 US$/tCO2-eq, which includes a small contribution from biofuels from cellulosic biomass. The potential strongly depends on production efficiency, the development of advanced techniques such as conversion of cellulose by
enzymatic processes or by gasification and synthesis, costs, and competition with other uses of land. Currently the cost and performance of ethanol in terms of CO2 emissions avoided is unfavourable, except for production from sugarcane in lowwage countries (Figure TS.16) (medium agreement, medium evidence) [5.3.1]. The economic and market potential of hydrogen vehicles remains uncertain. Electric vehicles with high efficiency (more than 90%), but low driving range and short battery life have a limited market penetration. For both options, the emissions are determined by the production of hydrogen and electricity. If hydrogen is produced from coal or gas with CCS (currently the cheapest way) or from biomass, solar, nuclear or wind energy, well-to-wheel carbon emissions could be nearly eliminated. Further technological advances and/or cost reductions would be required in fuel-cells, hydrogen storage, hydrogen or electricity production with low- or zero-carbon emissions, and batteries (high agreement, medium evidence) [5.3.1]. The total mitigation potential in 2030 of the energyefficiency options applied to light duty vehicles would be around 0.7–0.8 GtCO2-eq in 2030 at costs lower than 100 US$/tCO2. Data are not sufficient to provide a similar estimate for heavy-duty vehicles. The use of current and advanced biofuels, as mentioned above, would give an additional reduction potential of another 600–1500 MtCO2-eq
US $/l Biodiesel
Ethanol
1.0
Diesel Gasoline
0.8
0.6
0.4
2005
0.2
2030
er -T sy rop nt sc he h sis
Fi
sh
ta
ble
fa ve ge
an
im
al
los llu
oil
t
ic
t wh
be e
e aiz m
ea ce
su
Average crude oil price, US$/bbl
80
e
60
an
40
rc
20
ga
0
t
0
Figure TS.16: Comparison between current and future biofuel production costs versus gasoline and diesel ex-refinery (FOB) prices for a range of crude oil prices [Figure 5.9]. Note: prices exclude taxes.
50
Technical Summary
in 2030 at costs lower than 25 US$/tCO2 (low agreement, limited evidence) [5.4.2].
offset the growth in shipping activity over the same period (medium agreement, medium evidence) [5.3.4].
A critical threat to the potential for future reduction of CO2 emissions from use of fuel economy technologies is that they can be used to increase vehicle power and size rather than to improve the overall fuel economy and reduce carbon emissions. The preference of the market for power and size has consumed much of the potential for GHG mitigation reduction achieved over the past two decades. If this trend continues, it will significantly diminish the GHG mitigation potential of the advanced technologies described above (high agreement, much evidence) [5.2; 5.3].
Rail transport The main opportunities for mitigating GHG emissions associated with rail transport are improving aerodynamics, reduction of train weight, introducing regenerative braking and on-board energy storage and, of course, mitigating the GHG emissions from electricity generation. There are no estimates available of total mitigation potential and costs [5.3.2].
Air traffic The fuel efficiency of civil aviation can be improved by a variety of means including technology, operation and management of air traffic. Technology developments might offer a 20% improvement in fuel efficiency over 1997 levels by 2015, with a 40–50% improvement likely by 2050. As civil aviation continues to grow at around 5% each year, such improvements are unlikely to keep carbon emissions from global air travel from increasing. The introduction of biofuels could mitigate some of aviation’s carbon emissions, if biofuels can be developed to meet the demanding specifications of the aviation industry, although both the costs of such fuels and the emissions from their production process are uncertain at this time (medium agreement, medium evidence) [5.3.3]. Aircraft operations can be optimized for energy use (with minimum CO2 emissions) by minimizing taxiing time, flying at optimal cruise altitudes, flying minimum-distance great-circle routes, and minimizing holding and stacking around airports. The GHG-reduction potential of such strategies has been estimated at 6–12%. More recently, researchers have begun to address the potential for minimizing the total climate impact of aircraft operations, including ozone impacts, contrails and nitrogen oxides emissions. The mitigation potential in 2030 for aviation is 280 MtCO2/yr at costs <100 US$/tCO2 (medium agreement, medium evidence) [5.4.2]. Marine transport Since the TAR, an International Maritime Organization (IMO) assessment found that a combination of technical measures could reduce carbon emissions by 4–20% in older ships and 5–30% in new ships by applying state-of-the-art knowledge, such as hull and propeller design and maintenance. However, due to the long lifetime of engines, it will take decades before measures on existing ships are implemented on a significant scale. The short-term potential for operational measures, including route-planning and speed reduction, ranged from 1–40%. The study estimated a maximum reduction of emissions of the world fleet of about 18% by 2010 and 28% by 2020, when all measures were to be implemented. The data do not allow an estimate of an absolute mitigation potential figure and the mitigation potential is not expected to be sufficient to
Modal shifts and public transport Providing public transports systems and their related infrastructure and promoting non-motorized transport can contribute to GHG mitigation. However, local conditions determine how much transport can be shifted to less energyintensive modes. Occupancy rates and the primary energy sources of the transport modes further determine the mitigation potential [5.3.1]. The energy requirements of urban transport are strongly influenced by the density and spatial structure of the built environment, as well as by the location, extent and nature of the transport infrastructure. Large-capacity buses, light-rail transit and metro or suburban rail are increasingly being used for the expansion of public transport. Bus Rapid Transit systems have relatively low capital and operational costs, but it is uncertain if they can be implemented in developing countries with the same success as in South America. If the share of buses in passenger transport were to increase by 5–10%, then CO2 emissions would fall by 4-9% at costs in the order of US$ 60-70/tCO2 [5.3.1]. More than 30% of the trips made by cars in Europe are for less than 3 km and 50% for less than 5 km. Although the figures may differ for other continents, there is potential for mitigation by shifting from cars to non-motorized transport (walking and cycling), or preventing a growth of car transport at the expense of non-motorized transport. Mitigation potentials are highly dependent on local conditions, but there are substantial cobenefits in terms of air quality, congestion and road safety (high agreement, much evidence) [5.3.1]. Overall mitigation potential in the transport sector The overall potential and cost for CO2 mitigation can only be partially estimated due to lack of data for heavy-duty vehicles, rail transport, shipping and modal split change/ public transport promotion. The total economic potential for improved efficiency of light-duty vehicles and aeroplanes and substituting biofuels for conventional fossil fuels, for a carbon price up to 100 US$/ tCO2-eq, is estimated to be about 1600–2550 MtCO2. This is an underestimate of potential for mitigation in the transport sector (high agreement, medium evidence) [5.4.2].
51
Technical Summary
Effectiveness of and experience with climate policies, potentials, barriers and opportunities/ implementation issues Policies and measures for surface transport Given the positive effects of higher population densities on public transport use, walking, cycling and CO2 emissions, better integrated spatial planning is an important policy element in the transportation sector. There are some good examples for large cities in several countries. Transportation Demand Management (TDM) can be effective in reducing private vehicle travel if rigorously implemented and supported. Soft measures, such as the provision of information and the use of communication strategies and educational techniques have encouraged a change in personal behaviour leading to a reduction in the use of the car by 14% in an Australian city, 12% in a German city and 13% in a Swedish city (medium agreement, medium evidence) [5.5.1]. Fuel-economy standards or CO2 standards have been effective in reducing GHG emissions, but so far, transport growth has overwhelmed their impact. Most industrialized and some developing countries have set fuel-economy standards for new light-duty vehicles. The forms and stringency of standards vary widely, from uniform, mandatory corporate average standards, through graduated standards by vehicle weight class or size, to voluntary industry-wide standards. Fuel economy standards have been universally effective, depending on their stringency, in improving vehicle fuel economy, increasing on-road fleetaverage fuel economy and reducing fuel use and carbon emissions. In some countries, fuel-economy standards have been strongly opposed by segments of the automotive industry on a variety of grounds, ranging from economic efficiency to safety. The overall effectiveness of standards can be significantly enhanced if combined with fiscal incentives and consumer information (high agreement, much evidence) [5.5.1]. Taxes on vehicle purchase, registration, use and motor fuels, as well as road and parking pricing policies are important determinants of vehicle-energy use and GHG emissions. They are employed by different countries to raise general revenue, to partially internalize the external costs of vehicle use or to control congestion of public roads. An important reason for fuel or CO2 tax having limited effects is that price elasticities tend to be substantially smaller than the income elasticities of demand. In the long run, the income elasticity of demand is a factor 1.5–3 higher than the price elasticity of total transport demand, meaning that price signals become less effective with increasing incomes. Rebates on vehicle purchase and registration taxes for fuel-efficient vehicles have been shown to be effective. Road and parking pricing policies are applied in several cities, with marked effects on passenger car traffic (high agreement, much evidence) [5.5.1]. Many governments have introduced or are intending to implement policies to promote biofuels in national emission 52
abatement strategies. Since the benefit of biofuels for CO2 mitigation comes mainly from the well-to-tank part, incentives for biofuels are more effective climate policies if they are tied to entire well-to-wheels CO2 efficiencies. Thus preferential tax rates, subsidies and quotas for fuel blending should be calibrated to the benefits in terms of net CO2 savings over the entire well-to-wheel cycle associated with each fuel. In order to avoid the negative effects of biofuel production on sustainable development (e.g., biodiversity impacts), additional conditions could be tied to incentives for biofuels. Policies and measures for aviation and marine transport In order to reduce emissions from air and marine transport resulting from the combustion of bunker fuels, new policy frameworks need to be developed. Both the International Civil Aviation Organization (ICAO) and IMO have studied options for limiting GHG emissions. However, neither has yet been able to devise a suitable framework for implementing policies. ICAO, however, has endorsed the concept of an open, international emission-trading system implemented through a voluntary scheme, or the incorporation of international aviation into existing emission-trading systems. For aviation, both fuel or emission charges and trading would have the potential to reduce emissions considerably. The geographical scope (routes and operators covered), the amount of allowances to be allocated to the aviation sector and the coverage of non-CO2 climate impacts will be key design elements in determining the effectiveness of emissions trading for reducing the impacts of aviation on climate. Emission charges or trading would lead to an increase in fuel costs that will have a positive impact on engine efficiency [5.5.2]. Current policy initiatives in the shipping sector are mostly based on voluntary schemes, using indexes for the fuel efficiency of ships. Environmentally differentiated port dues are being used in a few places. Other policies to limit shipping emissions would be the inclusion of international shipping in international emissions-trading schemes, fuel taxes and regulatory instruments (high agreement, medium evidence) [5.5.2]. Integrated and non-climate policies affecting emissions of GHGs and co-benefits of GHG mitigation policies Transport planning and policy have recently placed more weight on sustainable development aspects. This includes reducing oil imports, improved air quality, reducing noise pollution, increasing safety, reducing congestion and improving access to transport facilities. Such policies can have important synergies with reducing GHG emissions (high agreement, medium evidence) [5.5.4; 5.5.5].
Technical Summary
6
Residential and commercial buildings
2.4% in Scenario A1B (high agreement, medium evidence) [6.2, 6.3].
Status of the sector and emission trends Mitigation technologies and practices In 2004, direct GHG emissions from the buildings sector (excluding emissions from electricity use) were about 5 GtCO2eq/yr (3 GtCO2-eq/yr CO2; 0.1 GtCO2-eq/yr N2O; 0.4 GtCO2eq/yr CH4 and 1.5 GtCO2-eq/yr halocarbons). The last figure includes F-gases covered by the Montreal protocol and about 0.1–0.2 GtCO2-eq/yr of HFCs. As mitigation in this sector includes many measures aimed at saving electricity, the mitigation potential is generally calculated including electricity saving measures. For comparison, emission figures of the building sector are often presented including emissions from electricity use in the sector . When including the emissions from electricity use, energy-related CO2 emissions from the buildings sector were 8.6 Gt/yr, or 33% of the global total in 2004. Total GHG emissions, including the emissions from electricity use, are then estimated at 10.6 Gt CO2eq/yr (high agreement, medium evidence) [6.2]. Future carbon emissions from energy use in buildings The literature for the buildings sector uses a mixture of baselines. Therefore, for this chapter, a building sector baseline was defined, somewhere between SRES B2 and A1B2, with 14.3 GtCO2-eq GHG emissions (including emissions from electricity use) in 2030. The corresponding emissions in the SRES B2 and A1B scenarios are 11.4 and 15.6 GtCO2. In the SRES B2 scenario (Figure TS.17), which is based on relatively lower economic growth, North America and Non-Annex I East Asia account for the largest portion of the increase in emissions. In the SRES A1B scenario, which shows rapid economic growth, all the CO2 emissions increase is in the developing world: Asia, Middle East and North Africa, Latin America, and Sub-Saharan Africa, in that order. Overall, average annual CO2 emission growth between 2004 and 2030 is 1.5% in Scenario B2 and 2
Measures to reduce GHG emissions from buildings fall into one of three categories: 1) reducing energy consumption13 and embodied energy in buildings; 2) switching to low-carbon fuels, including a higher share of renewable energy; 3) controlling emissions of non-CO2 GHG gases. Many current technologies allow building energy consumption to be reduced through better thermal envelopes14, improved design methods and building operations, more efficient equipment,and reductions in demand for energy services. The relative importance of heating and cooling depends on climate and thus varies regionally, while the effectiveness of passive design techniques also depends on climate, with important distinctions between hot-humid and hot-arid regions. Occupant behaviour, including avoiding unnecessary operation of equipment and adaptive rather than invariant temperature standards for heating and cooling, is also a significant factor in limiting building energy use (high agreement, much evidence) [6.4]. Mitigation potential of the building sector Substantial CO2 emission reduction from energy use in buildings can be achieved over the coming years compared with projected emissions. The considerable experience in a wide variety of technologies, practices and systems for energy efficiency and an equally rich experience with policies and programmes that promote energy efficiency in buildings lend considerable confidence to this view. A significant portion of these savings can be achieved in ways that reduce life-cycle costs, thus providing reductions in CO2 emissions that have a net negative cost (generally higher investment cost but lower operating cost) (high agreement, much evidence) [6.4; 6.5].
EECCA 4
2
2
0 1971
Central & Eastern Europe 2000
2000
2030
Non-Annex I South Asia
0 1971 0 1971
2000
2030
2
Non-Annex I East Asia
0 1971
2
2
Sub Saharan Africa
2000
2030
Middle East & North Africa
0 1971
0 1971 4
2030 0 1971
2000 2
2
North America
Western Europe
0 1971
2000
2030
2030 2 2
2000
2000
12
Pacific OECD
2030
2030 0 1971
World
Latin America
0 1971
2000
2030
8 2000
2030
4 0 1971
2000
2030
Figure TS.17: CO2 emissions (GtCO2) from buildings including emissions from the use of electricity, 1971–2030 [Figure 6.2]. Note: Dark red – historic emissions; light red – projection according to SRES B2 scenario. EECCA=Countries of Eastern Europe, the Caucasus and Central Asia.
13 14
This counts all forms of energy use in buildings, including electricity. The term ‘thermal envelope’ refers to the shell of a building as a barrier to unwanted heat or mass transfer between the interior of the building and outside.
53
Technical Summary
Table TS.5: GHG emissions reduction potential for the buildings stock in 2020a [Table 6.2].
Economic region
Countries/country groups reviewed for region
Potential as % of national baseline for buildingsb
Measures covering the largest potential
Measures providing the cheapest mitigation options
Developed countries
USA, EU-15, Canada, Greece, Australia, Republic of Korea, United Kingdom, Germany, Japan
Technical: 21%-54%c Economic (
1. Shell retrofit, inc. insulation, esp. windows and walls; 2. Space heating systems; 3. Efficient lights, especially shift to compact fluorescent lamps (CFL) and efficient ballasts.
1. Appliances such as efficient TVs and peripherals (both on-mode and standby), refrigerators and freezers, ventilators and air-conditioners; 2. Water heating equipment; 3. Lighting best practices.
Economies in Transition
Hungary, Russia, Poland, Croatia, as a group: Latvia, Lithuania, Estonia, Slovakia, Slovenia, Hungary, Malta, Cyprus, Poland, the Czech Republic
Technical: 26%-47%e Economic (
1. Pre- and post- insulation and replacement of building components, esp. windows; 2. Efficient lighting, esp. shift to CFLs; 3. Efficient appliances such as refrigerators and water heaters.
1. Efficient lighting and its controls; 2. Water and space heating control systems; 3. Retrofit and replacement of building components, esp. windows.
Developing countries
Myanmar, India, Indonesia, Argentine, Brazil, China, Ecuador, Thailand, Pakistan, South Africa
Technical: 18%-41% Economic (
1. Efficient lights, esp. shift to CFLs, light retrofit, and kerosene lamps; 2. Various types of improved cooking stoves, esp. biomass stoves, followed by LPG and kerosene stoves; 3. Efficient appliances such as air-conditioners and refrigerators.
1. Improved lights, esp. shift to CFLs light retrofit, and efficient kerosene lamps; 2. Various types of improved cooking stoves, esp. biomass based, followed by kerosene stoves; 3. Efficient electric appliances such as refrigerators and airconditioners.
Notes: a) Except for EU-15, Greece, Canada, India, and Russia, for which the target year was 2010, and Hungary, Ecuador and South Africa, for which the target was 2030. b) The fact that the market potential is higher than the economic potential for developed countries is explained by limitation of studies considering only one type of potential, so information for some studies likely having higher economic potential is missing. c) Both for 2010, if the approximate formula of Potential 2020 = 1 – ( 1 – Potential 2010)20/10 is used to extrapolate the potential as percentage of the baseline into the future (the year 2000 is assumed as a start year), this interval would be 38%–79%. d) Both for 2010, if suggested extrapolation formula is used, this interval would be 22%–44%. e) The last figure is for 2010, corresponds to 72% in 2020 if the extrapolation formula is used. f) The first figure is for 2010, corresponds to 24% in 2020 if the extrapolation formula is used. g) The last figure is for 2030, corresponds to 38% in 2020 if the suggested extrapolation formula is applied to derive the intermediate potential.
These conclusions are supported by a survey of 80 studies (Table TS.5), which show that efficient lighting technologies are among the most promising GHG-abatement measures in buildings in almost all countries, in terms of both costeffectiveness and potential savings. By 2020, approximately 760 Mt of CO2 emissions can be abated by the adoption of least life-cycle cost lighting systems globally, at an average cost of -160 US$/tCO2 (i.e., at a net economic benefit). In terms of the size of savings, improved insulation and district heating in the colder climates and efficiency measures related to space cooling and ventilation in the warmer climates come first in almost all studies, along with cooking stoves in developing countries. Other measures that rank high in terms of savings potential are solar water heating, efficient appliances and energy-management systems. As far as cost effectiveness is concerned, efficient cooking stoves rank second after lighting in developing countries, while the measures in second place in the industrialized countries 54
differ according to climatic and geographic region. Almost all the studies examining economies in transition (typically in cooler climates) found heating-related measures to be the most cost effective, including insulation of walls, roofs, windows and floors, as well as improved heating controls for district heating. In developed countries, appliance-related measures are typically identified as the most cost-effective, with upgrades of cooling-related equipment ranking high in warmer climates. Air-conditioning savings can be more expensive than other efficiency measures but can still be cost-effective, because they tend to displace more expensive peak power. In individual new buildings, it is possible to achieve 75% or more energy savings compared with recent current practice, generally at little or no extra cost. Realizing these savings requires an integrated design process involving architects, engineers, contractors and clients, with full consideration of opportunities for passively reducing the energy demands of buildings [6.4.1].
Technical Summary
Table TS.6: Global CO2 mitigation potential projections for 2020, as a function of costs [Table 6.3].
World regions
Baseline emissions in 2020
CO2 mitigation potentials as share of the baseline CO2 emission projections in cost categories in 2020 (costs in US$/tCO2-eq)
CO2 mitigation potentials in absolute values in cost categories in 2020, GtCO2-eq (costs in US$/tCO2-eq)
GtCO2-eq
<0
0-20
20-100
<100
<0
0-20
20-100
<100
Globe
11.1
29%
3%
4%
36%
3.2
0.35
0.45
4.0
OECD (-EIT)
4.8
27%
3%
2%
32%
1.3
0.10
0.10
1.6
EIT
1.3
29%
12%
23%
64%
0.4
0.15
0.30
0.85
Non-OECD
5.0
30%
2%
1%
32%
1.5
0.10
0.05
1.6
Note: The aggregated global potential as a function of cost and region is based on 17 studies that reported potentials in detail as a function of costs.
Addressing GHG mitigation in buildings in developing countries is of particular importance. Cooking stoves can be made to burn more efficiently and combust particles more completely, thus benefiting village dwellers through improved indoor-air quality, while reducing GHG emissions. Local sources of improved, low GHG materials can be identified. In urban areas, and increasingly in rural ones, there is a need for all the modern technologies used in industrialized countries to reduce GHG emissions [6.4.3]. Emerging areas for energy savings in commercial buildings include the application of controls and information technology to continuously monitor, diagnose and communicate faults in commercial buildings (‘intelligent control’); and systems approaches to reduce the need for ventilation, cooling, and dehumidification. Advanced windows, passive solar design, techniques for eliminating leaks in buildings and ducts, energyefficient appliances, and controlling standby and idle power consumption as well as solid-state lighting are also important in both residential and commercial sectors (high agreement, much evidence) [6.5]. Occupant behaviour, culture and consumer choice and use of technologies are major determinants of energy use in buildings and play a fundamental role in determining CO2 emissions. However, the potential reduction through non-technological options is rarely assessed and the potential leverage of policies over these is poorly understood (high agreement, medium evidence). There are opportunities to reduce direct emissions of fluorinated gases in the buildings sector significantly through the global application of best practices and recovery methods, with mitigation potential for all F-gases of 0.7 GtCO2-eq in 2015. Mitigation of halocarbon refrigerants mainly involves avoiding leakage from air conditioners and refrigeration equipment (e.g., during normal use, maintenance and at end of life) and reducing the use of halocarbons in new equipment. A key factor determining whether this potential will be realized is the costs associated with implementation of the measures to achieve the
emission reduction. These vary considerably, from a net benefit to 300 US$/tCO2-eq. (high agreement, much evidence) [6.5]. Mitigation potential of the building sector There is a global potential to reduce approximately 30% of the projected baseline emissions from the residential and commercial sectors cost effectively by 2020 (Table TS.6). At least a further 3% of baseline emissions can be avoided at costs up to 20 US$/tCO2-eq and 4% more if costs up to 100 US$/ tCO2-eq are considered. However, due to the large opportunities at low costs, the high-cost potential has only been assessed to a limited extent, and thus this figure is an underestimate. Using the global baseline emission projections for buildings15, these estimates represent a reduction of about 3.2, 3.6, and 4.0 Gtons of CO2-eq in 2020, at zero, 20 US$/tCO2-eq, and 100 US$/ tCO2-eq, respectively (high agreement, much evidence) [6.5]. The real potential is likely to be higher, because not all enduse efficiency options were considered by the studies; nontechnological options and their often significant co-benefits were omitted as were advanced integrated high-efficiency buildings. However, the market potential is much smaller than the economic potential. Given limited information for 2030, the 2020 findings for the economic potential to 2030 have been extrapolated to enable comparisons with other sectors. The estimates are given in Table TS.7. Extrapolation of the potentials to 2030 suggests that, globally, about 4.5, 5.0 and 5.6 GtCO2-eq/yr could be reduced at costs of <0, <20 and <100 US$/tCO2eq respectively. This is equivalent to 30, 35, and 40% of the projected baseline emissions. These figures are associated with significantly lower levels of certainty than the 2020 ones due to very limited research available for 2030 (medium agreement, low evidence). The outlook for the long-term future, assuming options in the building sector with a cost up to US$ 25/tCO2-eq, identifies a potential of about 7.7 GtCO2eq reductions in 2050.
15 The baseline CO2 emission projections were calculated on the basis of the 17 studies used for deriving the global potential (if a study did not contain a baseline, projections from another national mitigation report were used).
55
Technical Summary
Table TS.7: Global CO2 mitigation potential projections for 2030, as a function of cost, based on extrapolation from the 2020 numbers, in GtCO2 [Table 6.4].
Mitigation option
Region
Baseline projections in 2030
Potential costs at below 100 US$/tCO2-eq Low
High
Potential in different cost categories <0 US$/tCO2
0-20 US$/tCO2
20-100 US$/tCO2
<0 US$/tC
0-73 US$/tC
73-367 US$/tC
Electricity savingsa)
OECD EIT Non-OECD/EIT
3.4 0.40 4.5
0.75 0.15 1.7
0.95 0.20 2.4
0.85 0.20 1.9
0.0 0.0 0.1
0.0 0.0 0.1
Fuel savings
OECD EIT Non-OECD/EIT
2.0 1.0 3.0
1.0 0.55 0.70
1.2 0.85 0.80
0.85 0.20 0.65
0.2 0.2 0.1
0.1 0.3 0.0
Total
OECD EIT Non-OECD/EIT Global
5.4 1.4 7.5 14.3
1.8 0.70 2.4 4.8
2.2 1.1 3.2 6.4
1.7 0.40 2.5 4.5
0.2 0.2 0.1 0.5
0.1 0.3 0.0 0.7
Note: a) The absolute values of the potentials resulting from electricity savings in Table TS.8 and Chapter 11, Table 11.3 do not coincide due to application of different baselines; however, the potential estimates as percentage of the baseline are the same in both cases. Also Table 11.3 excludes the share of emission reductions which is already taken into account by the energy supply sector, while Table TS.7 does not separate this potential.
Interactions of mitigation options with vulnerability and adaptation
Effectiveness of and experience with policies for reducing CO2 emissions from energy use in buildings
If the world experiences warming, energy use for heating in temperate climates will decline (e.g., Europe, parts of Asia and North America), and for cooling will increase in most world regions. Several studies indicate that, in countries with moderate climates, the increase in electricity for additional cooling will outweigh the decrease for heating, and in Southern Europe a significant increase in summer peak demand is expected. Depending on the generation mix in particular countries, the net effect of warming on CO2 emissions may be an increase even where overall demand for final energy declines. This causes a positive feedback loop: more mechanical cooling emits more GHGs, thereby exacerbating warming (medium agreement, medium evidence).
Realizing such emissions reductions up to 2020 requires the rapid design, implementation and enforcement of strong policies promoting energy efficiency for buildings and equipment, renewable energy (where cost-effective), and advanced design techniques for new buildings (high agreement, much evidence) [6.5].
Investments in the buildings sector may reduce the overall cost of climate change by simultaneously addressing mitigation and adaptation. The most important of these synergies includes reduced cooling needs or energy use through measures such as application of integrated building design, passive solar construction, heat pumps with high efficiency for heating and cooling, adaptive window glazing, high-efficiency appliances emitting less waste heat, and retrofits including increased insulation, optimized for specific climates, and storm-proofing. Appropriate urban planning, including increasing green areas as well as cool roofs in cities, has proved to be an efficient way of limiting the ‘heat island’ effect, thereby reducing cooling needs and the likelihood of urban fires. Adaptive comfort, where occupants accept higher indoor (comfort) temperatures when the outside temperature is high, is now often incorporated in design considerations (high agreement, medium evidence) [6.9].
56
There are, however, substantial barriers that need to be overcome to achieve the high indicated negative and low cost mitigation potential. These include hidden costs, mismatches between incentives and benefits (e.g., between landlords and tenants), limitations in access to financing, subsidies on energy prices, as well as fragmentation of the industry and the design process. These barriers are especially strong and diverse in the residential and commercial sectors; overcoming them is therefore only possible through a diverse portfolio of policy instruments combined with good enforcement (high agreement, medium evidence). A wide range of policies has been shown in many countries to be successful in cutting GHG emissions from buildings. Table TS.8 summarizes the key policy tools applied and compares them according to the effectiveness of the policy instrument, based on selected best practices. Most instruments reviewed can achieve significant energy and CO2 savings. In an evaluation of 60 policy evaluations from about 30 countries, the highest CO2 emission reductions were achieved through building codes, appliance standards and tax-exemption policies. Appliance standards, energy-efficiency obligations and quotas, demand-side management programmes and mandatory labelling were found to be among the most cost-effective policy tools. Subsidies and energy or carbon taxes were the least costeffective instrument. Information programmes are also cost
Technical Summary
Table TS.8: The impact and effectiveness of selected policy instruments aimed at mitigating GHG emissions in the buildings sector using best practices [Table 6.6].
Policy instrument
Emission reduction effectivenessa
Costeffectivenessb
Special conditions for success, major strengths and limitations, co-benefits
Appliance standards
High
High
Factors for success: periodic update of standards, independent control, information, communication and education.
Building codes
High
Medium
No incentive to improve beyond target. Only effective if enforced.
Public leadership programmes, inc. procurement regulations
High
High/Medium
Can be used effectively to demonstrate new technologies and practices. Mandatory programmes have higher potential than voluntary ones. Factor for success: ambitious energy efficiency labelling and testing.
Energy efficiency obligations and quotas
High
High
Continuous improvements necessary: new EE measures, short term incentives to transform markets, etc.
Demand-side management programmes
High
High
Tend to be more cost-effective for commercial sector than for residences.
Energy performance High contracting/ESCO supportC
Medium
Strength: no need for public spending or market intervention, cobenefit of improved competitiveness.
Energy efficiency certificate schemes
Medium
Medium
No long-term experience. Transaction costs can be high. Institutional structures needed. Profound interactions with existing policies. Benefits for employment.
Kyoto Protocol flexible mechanismsd
Low
Low
So far limited number of CDM &JI projects in buildings.
Taxation (on CO2 or fuels)
Low
Low
Effect depends on price elasticity. Revenues can be earmarked for further efficiency. More effective when combined with other tools.
Tax exemptions/ reductions
High
High
If properly structured, stimulate introduction of highly efficient equipment and new buildings.
Capital subsidies, grants, subsidised loans
High
Low
Positive for low-income households, risk of free-riders, may induce pioneering investments.
Labelling and certification programmes
Medium/High
High
Mandatory programmes more effective than voluntary ones. Effectiveness can be boosted by combination with other instruments and regular updates.
Voluntary and negotiated agreements
Medium/High
Medium
Can be effective when regulations are difficult to enforce. Effective if combined with financial incentives, and threat of regulation.
Education and information programmes
Low/Medium
High
More applicable in residential sector than commercial. Success condition: best applied in combination with other measures.
Mandatory audit and energy High, but variable management requirement
Medium
Most effective if combined with other measures such as financial incentives.
Detailed billing and disclosure programmes
Medium
Success conditions: combination with other measures and periodic evaluation.
Medium
Notes: a) includes ease of implementation; feasibility and simplicity of enforcement; applicability in many locations; and other factors contributing to overall magnitude of realized savings. b) Cost-effectiveness is related to specific societal cost per carbon emissions avoided. c) Energy service companies. d) Joint Implementation, Clean Development Mechanism, International Emissions Trading (includes the Green Investment Scheme).
effective, particularly when they accompany most other policy measures (medium agreement, medium evidence) [6.8]. Policies and measures that aim at reducing leakage or discourage the use of refrigerants containing fluorine may reduce emissions of F-gases substantially in future years (high agreement, medium evidence) [6.8.4]. The limited overall impact of policies so far is due to several factors: 1) slow implementation processes; 2) the lack of regular
updating of building codes (requirements of many policies are often close to common practices, despite the fact that CO2neutral construction without major financial sacrifices is already possible) and appliance standards and labelling; 3) inadequate funding; 4) insufficient enforcement. In developing countries and economies in transition, implementation of energy-efficiency policies is compromised by a lack of concrete implementation combined with poor or non-existent enforcement mechanisms. Another challenge is to promote GHG-abatement measures for the building shell of existing buildings due to the long time 57
Technical Summary
periods between regular building retrofits and the slow turnover of buildings in developed countries (high agreement, much evidence) [6.8]. Co-benefits and links to sustainable development Energy efficiency and utilization of renewable energy in buildings offer synergies between sustainable development and GHG abatement. The most relevant of these for the least developed countries are safe and efficient cooking stoves that, while cutting GHG emissions, significantly reduce mortality and morbidity by reducing indoor air pollution. Safe and efficient cooking stoves also reduce the workload for women and children who typically gather the fuel for traditional stoves and decrease the demands on scarce natural resources. Reduction in outdoor air pollution is another significant co-benefit. In general, in developed and developing countries, improved energy efficiency in buildings and the clean and efficient use of locally available renewable energy resources results in: • substantial savings in energy-related investment, since efficiency is less costly than new supply; • funds freed up for other purposes, such as infrastructure investments; • improved system reliability and energy security; • increased access to energy services; • reduced fuel poverty; • improvement of local environmental quality; • positive effects on employment, by creating new business opportunities and through the multiplier effects of spending money saved on energy costs in another way. There is increasing evidence that well-designed energy-efficient buildings often promote occupant productivity and health (high agreement, medium evidence) [6.9]. Support from industrialized countries for the development and implementation of policies to increase energy efficiency of buildings and equipment in developing countries and economies in transition could contribute substantially to reductions in the growth of CO2 emissions and improve the welfare of the population. Devoting international aid or other public and private funds aimed at sustainable development to energy efficiency and renewable energy initiatives in buildings can achieve a multitude of development objectives and result in long-lasting impacts. The transfer of knowledge, expertise and know-how from developed to developing countries can facilitate the adoption of photovoltaics (PV), including PV-powered light emitting diode-based (LED) lighting, high-insulation building materials, efficient appliances and lighting, integrated design, building energy-management systems, and solar cooling. However, capital financing will also be needed [6.8.3].
Technology research, development, deployment, diffusion and transfer Although many practical and cost-effective technologies and practices are available today, research and development is needed in such areas as: high-performance control systems16; advanced window glazing; new materials for insulated panels; various systems to utilize passive and other renewable energy sources; phase-change materials to increase thermal storage; high-performance ground-source reversible heat pumps; integrated appliances and other equipment to use waste heat; novel cooling technologies, and the use of community-wide networks to supply heating, cooling and electricity to buildings. Demonstrations of these technologies and systems, and training of professionals, are necessary steps toward bringing those new technologies to market [6.8.3]. Long-term-outlook Long-term GHG reduction in buildings needs to start soon because of the slow turnover of the building stock. To achieve large-scale savings in new buildings in the longer term, new approaches to integrated design and operation of buildings need to be taught, spread, and put into large-scale practice as soon as possible. Such training is currently not available for the majority of professionals in the building industry. Because of the important role of non-technological opportunities in buildings, ambitious GHG reductions may require a cultural shift towards a society that embraces climate protection and sustainable development among its fundamental values, leading to social pressure for building construction and use with much reduced environmental footprints (high agreement, medium evidence) [6.4.1; 6.8.1].
7
Industry
Status of the sector, development trends and implications Energy-intensive industries, iron and steel, non-ferrous metals, chemicals and fertilizer, petroleum-refining, cement, and pulp and paper, account for about 85% of the industry sector’s energy consumption in most countries. Since energy use in other sectors grew faster, the sector’s share in global primary energy use declined from 40% in 1971 to 37% in 2004 [7.1.3]. Much of this energy-intensive industry is now located in developing countries. Overall, in 2003, developing countries accounted for 42% of global steel production, 57% of global nitrogen fertilizer production, 78% of global cement manufacture, and about 50% of global aluminium production. In 2004, developing countries accounted for 46% of final energy
16 Advanced control systems need to be created that permit the integration of all energy service functions in the design and subsequent operation of commercial buildings (‘intelligent control’).
58
Technical Summary
4
EECCA 4
2
Western Europe
0 1971
2000
2030
Central & Eastern 2 Europe 0 1971
2000
2
2030
Non-Annex I South Asia
0 1971
2000
2030 0 1971
Non-Annex I East Asia
0 1971
Sub Saharan Africa
0 1971
4
2000
0 1971
2 2
2030
2 0 1971
2 Middle East & North Africa 2000
2000
2000
2030
2030 2
14
2030 2
2000
North America
2
Pacific OECD
2030
Latin America
0 1971
2000
2030
World
10 0 1971
2000
2030
6 2 1971
2000
2030
Figure TS.18: Industrial sector energy-related CO2 emissions (GtCO2; including electricity use), 1971–2030. [Table 7.1, 7.2]. Note: Dark red – historic emissions; light red – projections according to SRES B2 scenario. Data extracted from Price et al. (2006). EECCA = Countries of Eastern Europe, the Caucasus and Central Asia.
use by industry, developed country for 43% and economies in transition for 11%. Many facilities (for aluminium, cement and fertilizer industries) in developing nations are new and include the latest technology with lowest specific energy use. However, as in industrialized countries, many older, inefficient facilities remain. This creates a huge demand for investment in developing countries to improve energy efficiency and achieve emission reductions. The strong growth of energy-intensive industries during the 20th century is expected to continue as population and GDP increase [7.1.2; 7.1.3]. Though large-scale production dominates these energyintensive industries globally, small- and medium-sized enterprises (SMEs) have significant shares in many developing countries. While regulations and international competition are moving large industrial enterprises towards the use of environmentally sound technology, SMEs may not have the economic or technical capacity to install the necessary control equipment or are slower to innovate. These SME limitations create special challenges for efforts to mitigate GHG emissions (high agreement, much evidence) [7.1.1]. Emission trends (global and regional) Direct GHG emissions from industry are currently about 7.2 GtCO2-eq. As the mitigation options discussed in this chapter include measures aimed at reducing the industrial use of electricity, emissions including those from electricity use are important for comparison. Total industrial sector GHG emissions were about 12 GtCO2-eq in 2004, about 25% of the global total. CO2 emissions (including electricity use) from the industrial sector grew from 6.0 GtCO2 in 1971 to 9.9 GtCO2 in 2004. In 2004, developed nations accounted for 35% of total energy-related CO2 emissions, economies in transition for 11% and developing nations for 53% (see Figure TS.18). Industry also emits CO2 from non-energy uses of fossil fuels and from non-fossil fuel sources. In 2000,
these were estimated to total 1.7 GtCO2 (high agreement, much evidence) [7.1.3]. Industrial processes also emit other GHGs, including HFC23 from the manufacture of HCFC-22; PFCs from aluminium smelting and semiconductor processing; SF6 from use in flat panel screens (liquid crystal display) and semi-conductors, magnesium die casting, electrical equipment, aluminium melting, and others, and CH4 and N2O from chemical industry sources and food-industry waste streams. Total emission from these sources was about 0.4 GtCO2-eq in 2000 (medium agreement, medium evidence) [7.1.3]. The projections for industrial CO2 emissions for 2030 under the SRES-B22 scenarios are around 14 GtCO2 (including electricity use) (see Figure TS.18). The highest average growth Table TS.9: Projected industrial sector emissions of non-CO2 GHGs, MtCO2-eq/yr [Table 7.3]. Region
1990
2000
2010
2030
Pacific OECD
38
53
47
49
North America
147
117
96
147
Western Europe
159
96
92
109
Central and Eastern Europe
31
21
22
27
EECCA
37
20
21
26
Developing Asia
34
91
118
230
Latin America
17
18
21
38
Sub Saharan Africa
6
10
11
21
Middle East and North Africa
2
3
10
20
470
428
438
668
World
Note: Emissions from refrigeration equipment used in industrial processes included; emissions from all other refrigeration and air-conditioning applications excluded. EECCA = the countries of Eastern Europe, the Caucasus and Central Asia.
59
60
Efficient pulping, Efficient drying, Shoe press, Condebelt drying
Efficient drying, Membranes
Pulp and paper
Food Biogas, Natural gas
Biomass, Landfill gas
Natural gas
Anaerobic digestion, Gasification
Black liquor gasification combined cycle
Air bottoming cycle
Biomass, By-products, Solar drying
Biomass fuels (bark, black liquor)
n/a
Biomass fuels, Biogas
Cullet preheating Oxyfuel furnace
Drying with gas turbine, power recovery
Recycling, Non-wood fibres
Increased cullet use
Slags, pozzolanes
Bio-feedstock
Glass
Waste fuels, Biogas, Biomass
Biofuels
Precalciner kiln, Roller mill, fluidized bed kiln
Pressure recovery turbine, hydrogen recovery
Cement
Natural gas
Membrane separation Refinery gas
Petroleum refining
Pre-coupled gas turbine, Pressure recovery turbine, H2 recovery
Scrap
Recycled plastics, biofeedstock
Natural gas
Charcoal
Recycled inputs
Membrane separations, Reactive distillation
Top-gas pressure recovery, By-product gas combined cycle
Renewables Biomass, Biogas, PV, Wind turbines, Hydropower
Chemicals
Natural gas, oil or plastic injection into the BF
Cogeneration
Feedstock change
Scrap
Smelt reduction, Near net shape casting, Scrap preheating, Dry coke quenching
Iron & steel
Coal to natural gas and oil
Power recovery
Non-ferrous Inert anodes, metals Efficient cell designs
Energy efficiency
Benchmarking; Energy management systems; Efficient motor systems, boilers, furnaces, lighting and heating/ventilation/air conditioning; Process integration
Sector
Sector wide
Fuel switching
Fibre orientation, Thinner paper
High-strength thin containers
Blended cement Geo-polymers
Linear low density polyethylene, high-perf. plastics
High strength steel
Product change
Reduction process losses, Closed water use
Reduction cutting and process losses
Recycling
(reduction in transport not included here)
Recycling, Thinner film and coating, Reduced process losses
Recycling, thinner film and coating
Recycling, High strength steel, Reduction process losses
Material efficiency
Table TS.10: Examples of industrial technology for reducing GHG emissions (not comprehensive). Technologies in italics are under demonstration or development [Table 7.5].
n/a
n/a
n/a
Control technology for N2O/CH4
N2O, PFCs, CFCs and HFCs control
PFC/SF6 controls
n/a
Non-CO2 GHG
Oxyfuel combustion in lime kiln
OxyfuelL combustion
Oxyfuel combustion in kiln
From hydrogen production
CO2 storage from ammonia, ethylene oxide processes
Hydrogen reduction, oxygen use in blast furnaces
Oxy-fuel combustion, CO2 separation from flue gas
CO2 capture and storage
Technical Summary
Technical Summary
rates in industrial-sector CO2 emissions are projected for developing countries. Growth in the regions of Central and Eastern Europe, the Caucasus and Central Asia, and Developing Asia is projected to slow in both scenarios for 2000–2030. CO2 emissions are expected to decline in the Pacific OECD, North America and Western Europe regions for B2 after 2010. For non-CO2 GHG emissions from the industrial sector, emissions by 2030 are projected to increase globally by a factor of 1.4, from 470 MtCO2-eq. (130 MtC-eq) in 1990 to 670 MtCO2-eq (180 MtC-eq.) in 2030 assuming no further action is taken to control these emissions. Mitigation efforts led to a decrease in non-CO2 GHG emissions between 1990 and 2000, and many programmes for additional control are underway (see Table TS.9) (high agreement, medium evidence) [7.1.3]. Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability Historically, the industrial sector has achieved reductions in energy intensity and emission intensity through adoption of energy efficiency and specific mitigation technologies, particularly in energy-intensive industries. The aluminium industry reported >70% reduction in PFC-emission intensity over the period 1990–2004 and the ammonia industry reported that plants designed in 2004 have a 50% reduction in energy intensity compared with those designed in 1960. Continuing to modernize ammonia-production facilities around the world will result in further energy-efficiency improvements. Reductions in refining energy intensity have also been reported [7.4.2, 7.4.3, 7.4.4]. The low technical and economic capacity of SMEs pose challenges for the diffusion of sound environmental technology, though some innovative R&D is taking place in SMEs. A wide range of measures and technologies have the potential to reduce industrial GHG emissions. These technologies can be grouped into the categories of energy efficiency, fuel switching, power recovery, renewables, feedstock change, product change and material efficiency (Table TS.10). Within each category, some technologies, such as the use of more efficient electric motors, are broadly applicable across all industries, while others, such as top-gas pressure recovery in blast furnaces, are process-specific. Later in the period to 2030, there will be a substantial additional potential from further energy- efficiency improvements and application of Carbon Capture and Storage (CCS)17 and nonGHG process technologies. Examples of such new technologies that are currently in the R&D phase include inert electrodes for aluminium manufacture and hydrogen for metal production (high agreement, much evidence) [7.2, 7.3, 7.4].
Mitigation potentials and costs in 2030 have been estimated in an industry-by-industry assessment of energy-intensive industries and an overall assessment of other industries. The approach yielded mitigation potentials of about 1.1 GtCO2-eq at a cost of <20 US$/tCO2 (74 US$/tC-eq); about 3.5 GtCO2eq at costs below <50 US$/tCO2 (180 US$/tC-eq); and about 4 GtCO2-eq/yr (0.60–1.4 GtC-eq/yr) at costs
17 See IPCC Special Report on CO2 Capture and Storage
61
Technical Summary
access and absorb information about available options (high agreement, much evidence) [7.9.1].
Integrated and non-climate policies affecting emissions of greenhouse gases
Voluntary agreements between industry and government to reduce energy use and GHG emissions have been used since the early 1990s. Well-designed agreements, which set realistic targets and have sufficient government support, often as part of a larger environmental policy package, and a real threat of increased government regulation or energy/GHG taxes if targets are not achieved, can provide more than businessas-usual energy savings or emission reductions. Some have accelerated the application of best available technology and led to reductions in emissions compared with the baseline, particularly in countries with traditions of close cooperation between government and industry. However, the majority of voluntary agreements have not achieved significant emission reductions beyond business-as-usual. Corporations, subnational governments, non-government organizations (NGOs) and civil groups are adopting a wide variety of voluntary actions, independent of government authorities, which may limit GHG emissions, stimulate innovative policies, and encourage the deployment of new technologies. By themselves, however, they generally have limited impact.
Policies aimed at balancing energy security, environmental protection and economic development can have a positive or negative impact on mitigation. Sustainable development policies focusing on energy efficiency, dematerialization, and use of renewables support GHG mitigation objectives. Wastemanagement policies reduce industrial sector GHG emissions by reducing energy use through the re-use of products. Airpollutant reduction measures can have synergy with GHGemissions reduction when reduction is achieved by shifting to low-carbon fuels, but do not always reduce GHG emissions as many require the use of additional energy.
Policies that reduce the barriers to adoption of cost-effective, low-GHG emission technologies (e.g., lack of information, absence of standards and unavailability of affordable financing for first purchases of modern technology) can be effective. Many countries, both developed and developing, have financial schemes available to promote energy saving in industry. According to a World Energy Council survey, 28 countries provide some sort of grant or subsidy for industrial energyefficiency projects. Fiscal measures are also frequently used to stimulate energy savings in industry. However, a drawback to financial incentives is that they are often also used by investors who would have made the investment without the incentive. Possible solutions to improve cost-effectiveness are to restrict schemes to specific target groups and/or techniques (selected lists of equipment, only innovative technologies), or use a direct criterion of cost-effectiveness [7.9.3]. Several national, regional or sectoral CO2 emissions trading systems either exist or are being developed. The further refinement of these trading systems could be informed by evidence that suggests that in some important aspects, participants from industrial sectors face a significantly different situation to those from the electricity sector. For instance, responses to carbon emission price in industry tend to be slower because of the more limited technology portfolio and absence of short-term fuel-switching possibilities, making predictable allocation mechanisms and stable price signals a more important issue for industry [7.9.4]. As noted in the TAR, industrial enterprises of all sizes are vulnerable to changes in government policy and consumer preferences. That is why a stable policy regime is so important for industry (high agreement, much evidence) [7.9]. 62
In addition to implementing the mitigation options discussed above, achieving sustainable development will require industrial development pathways that minimize the need for future mitigation (high agreement, medium evidence). Large companies have greater resources, and usually more incentives, to factor environmental and social considerations into their operations than small and medium enterprises (SMEs), but SMEs provide the bulk of employment and manufacturing capacity in many countries. Integrating SME development strategy into broader national strategies for development is consistent with sustainable development objectives. Energyintensive industries are now committing to a number of measures towards human capital development, health and safety, community development etc., which are consistent with the goal of corporate social responsibility (high agreement, much evidence) [7.7; 7.8]. Co-benefits of greenhouse gas mitigation policies The co-benefits of industrial GHG mitigation include: reduced emissions of air pollutants, and waste (which in turn reduce environmental compliance and waste disposal costs), increased production and product quality, lower maintenance and operating costs, an improved working environment, and other benefits such as decreased liability, improved public image and worker morale, and delaying or reducing capital expenditures. The reduction of energy use can indirectly contribute to reduced health impacts of air pollutants particularly where no air-pollution regulation exists (high agreement, much evidence) [7.10]. Technology research, development, deployment, diffusion and transfer Commercially available industrial technology provides a very large potential to reduce GHG emissions. However, even with the application of this technology, many industrial processes would still require much more energy than the thermodynamic ideal, suggesting a large additional potential for energy-efficiency improvement and GHG mitigation potential. In addition, some industrial processes emit GHGs that are independent of heat and power use. Commercial technology to eliminate these emissions does not currently exist for some of
Technical Summary
these processes, for example, development of an inert electrode to eliminate process emissions from aluminium manufacture and the use of hydrogen to reduce iron and non-ferrous metal ores. These new technologies must also meet a host of other criteria, including cost competitiveness, safety and regulatory requirements, as well as winning customer acceptance. Industrial technology research, development, deployment and diffusion are carried out both by governments and companies, ideally in complementary roles. Because of the large economic risks inherent in technologies with GHG emission mitigation as the main purpose, government programmes are likely to be needed in order to facilitate a sufficient level of research and development. It is appropriate for governments to identify fundamental barriers to technology and find solutions to overcome these barriers, but companies should bear the risks and capture the rewards of commercialization.
Production of food and fibre has more than kept pace with the sharp increase in demand in a more populated world, so that the global average daily availability of calories per capita has increased, though with regional exceptions. However, this growth has been at the expense of increasing pressure on the environment and dwindling natural resources, and has not solved problems of food security and widespread child malnutrition in poor countries (high agreement, much evidence).
In addition, government information, energy audits, reporting, and benchmarking programmes promote technology transfer and diffusion. The key factors determining private-sector technology deployment and diffusion are competitive advantage, consumer acceptance, country-specific characteristics, protection of intellectual property rights, and regulatory frameworks (medium agreement, medium evidence) [7.11].
Economic growth and changing lifestyles in some developing countries are causing a growing demand for meat and dairy products. From 1967–1997, meat demand in developing countries rose from 11 to 24 kg per capita per year, achieving an annual growth rate of more than 5% by the end of that period. Further increases in global meat demand (about 60% by 2020) are projected, mostly in developing regions such as South and Southeast Asia, and Sub-Saharan Africa (medium agreement, much evidence) [8.2].
Long-term outlook Many technologies offer long-term potential for mitigating industrial GHG emissions, but interest has focused on three areas: biological processing, use of hydrogen and nanotechnology. Given the complexity of the industrial sector, achieving low GHG emissions is the sum of many cross-cutting and individual sector transitions. Because of the speed of capital stock turnover in at least some branches of industry, inertia by ‘technology lock-in’ may occur. Retrofitting provides opportunities in the meantime, but basic changes in technology occur only when the capital stock is installed or replaced (high agreement, much evidence) [7.12].
8
The absolute area of global arable land has increased to about 1400 Mha, an overall increase of 8% since the 1960s (5% decrease in developed countries and 22% increase in developing countries). This trend is expected to continue into the future, with a projected additional 500 Mha converted to agriculture from 1997–2020, mostly in Latin America and Sub-Saharan Africa (medium agreement, limited evidence).
Emission trends For 2005, agriculture accounted for an estimated emission of 5.1 to 6.1 GtCO2-eq (10–12% of total global anthropogenic emissions of GHGs). CH4 contributed 3.3 GtCO2-eq and N2O 2.8 GtCO2-eq. Of global anthropogenic emissions in 2005, agriculture accounted for about 60% of N2O and about 50% of CH4 (medium agreement, medium evidence). Despite large annual exchanges of CO2 between the atmosphere and agricultural lands, the net flux is estimated to be approximately balanced, with net CO2 emissions of only around 0.04 GtCO2/ yr (emissions from electricity and fuel use in agriculture are covered in the buildings and transport sector respectively) (low agreement, limited evidence) [8.3].
Agriculture
Status of the sector, future trends in production and consumption, and implications Technological developments have allowed remarkable progress in agricultural output per unit of land, increasing per capita food availability despite a consistent decline in per capita agricultural land area (high agreement, much evidence). However, progress has been uneven across the world, with rural poverty and malnutrition remaining in some countries. The share of animal products in the diet has increased progressively in developing countries, while remaining constant in the developed world (high agreement, much evidence).
Trends in GHG emissions in agriculture are responsive to global changes: increases are expected as diets change and population growth increases food demand. Future climate change may eventually release more soil carbon (though the effect is uncertain as climate change may also increase soil carbon inputs through high production). Emerging technologies may permit reductions of emissions per unit of food produced, but absolute emissions are likely to grow (medium agreement, medium evidence). Without additional policies, agricultural N2O and CH4 emissions are projected to increase by 35–60% and ~60%, respectively, to 2030, thus increasing more rapidly than the 14% increase of non-CO2 GHG observed from 1990 to 2005 (medium agreement, limited evidence) [8.3.2]. 63
Technical Summary
1000
Western Europe
0 1990
2020
500
0 1990
EECCA 1000
Central and 500 Eastern Europe
0 1990
2000 Non-Annex I East Asia
2020
Middle East and 500 North Africa 0 1990
Sub-Saharan Africa
0 1990
2020
1000
1000
2000
Non-Annex I South Asia
0 1990
1000
0 1990
2020
OECD North America
2020
0 1990
Latin America & The Caribbean
2020
2020
1000 500
OECD Pacific
0 1990
2020
8000
World
0 1990
2020
2020
4000 0 1990
2020
Figure TS.19: Historic and projected N2O and CH4 emissions (MtCO2-eq.) in the agricultural sector of ten world regions, 1990–2020 [Figure 8.2]. Note: EECCA=Countries of Eastern Europe, the Caucasus and Central Asia.
Both the magnitude of the emissions and the relative importance of the different sources vary widely among world regions (Figure TS.19). In 2005, the group of five regions consisting mostly of non-Annex I countries were responsible for 74% of total agricultural emissions [8.3]. Mitigation technologies, practices, options, potentials and costs Considering all gases, the economic potentials for agricultural mitigation by 2030 are estimated to be about 1600, 2700 and 4300 MtCO2-eq/yr at carbon prices of up to 20, 50 and 100 US$/ tCO2-eq, respectively for a SRES B2 baseline (see Table TS.11) (medium agreement, limited evidence) [8.4.3]. Improved agricultural management can reduce net GHG emissions, often affecting more than one GHG. The effectiveness of these practices depends on factors such as climate, soil type and farming system (high agreement, much evidence). About 90% of the total mitigation arises from sink enhancement (soil C sequestration) and about 10% from emission reduction (medium agreement, medium evidence). The most prominent mitigation options in agriculture (with potentials shown in Mt
CO2eq/yr for carbon prices up to 100 US$/tCO2-eq by 2030) are (see also Figure TS.20): • restoration of cultivated organic soils (1260) • improved cropland management (including agronomy, nutrient management, tillage/residue management and water management (including irrigation and drainage) and set-aside / agro-forestry (1110) • improved grazing land management (including grazing intensity, increased productivity, nutrient management, fire management and species introduction (810) • restoration of degraded lands (using erosion control, organic amendments and nutrient amendments (690). Lower, but still substantial mitigation potential is provided by: • rice management (210) • livestock management (including improved feeding practices, dietary additives, breeding and other structural changes, and improved manure management (improved storage and handling and anaerobic digestion) (260) (medium agreement, limited evidence). In addition, 770 MtCO2-eq/yr could be provided by 2030 by improved energy efficiency in agriculture. This amount is, however, for a large part included in the mitigation potential of buildings and transport [8.1; 8.4].
Table TS.11: Estimates of global agricultural economic GHG mitigation potential (MtCO2-eq/yr) by 2030 under different assumed carbon prices for a SRES B2 baseline [Table 8.7].
Carbon price (US$/tCO2-eq) Up to 20
Up to 50
Up to 100
OECD
330 (60-470)
540 (300-780)
870 (460-1280)
EIT
160 (30-240)
270 (150-390)
440 (230-640)
1140 (210-1660)
1880 (1040-2740)
3050 (1610-4480)
Non-OECD/ EIT
Note: figures in brackets show standard deviation around the mean estimate, potential excluding energy-efficiency measures and fossil fuel offsets from bioenergy.
64
At lower carbon prices, low cost measures most similar to current practice are favoured (e.g., cropland management options), but at higher carbon prices, more expensive measures with higher mitigation potentials per unit area are favoured (e.g., restoration of cultivated organic / peaty soils; Figure TS.20) (medium agreement, limited evidence) [8.4.3]. GHG emissions could also be reduced by substitution of fossil fuels by energy production from agricultural feedstocks (e.g., crop residues, dung, energy crops), which are counted in energy end-use sectors (particularly energy supply and transport). There are no accurate estimates of future agricultural biomass supply, with figures ranging from 22 EJ/yr in 2025
Technical Summary
1400
Mt CO2-eq/yr up to 20 US$/tCO2-eq. up to 50 US$/tCO2-eq. up to 100 US$/tCO2-eq.
1200 1000 800 600 400 200
na ma ge nu me re nt ma
k
t-a si ag de, ro LU for C es & try
se
toc es liv
me rice nt ge ma
na
ed rest lan ore ds ad gr de
g ma raz na ing ge lan me d nt
na crop ge lan me d nt ma
re
sto re or cu ga ltiv nic at so ed ils
0
Mitigation measure Figure TS.20: Potential for GHG agricultural mitigation in 2030 at a range of carbon prices for a SRES B2 baseline [Figure 8.9]. Note: B2 scenario shown, though the pattern is similar for all SRES scenarios. Energy-efficiency measures (770 MtCO2-eq) are included in the mitigation potential of the buildings and energy sector.
to more than 400 EJ/yr in 2050. The actual contribution of agriculture to the mitigation potential by using bioenergy depends, however, on the relative prices of fuels and the balance of demand and supply. Top-down assessments that include assumptions on such a balance estimate the economic mitigation potential of biomass energy supplied from agriculture to be 70–1260 MtCO2-eq/yr at up to 20 US$/ tCO2-eq, and 560–2320 MtCO2-eq/yr at up to 50 US$/tCO2eq. There are no estimates for the additional potential from top-down models at carbon prices up to 100 US$/tCO2-eq, but the estimate for prices above 100 US$/tCO2-eq is 2720 MtCO2-eq/yr. These potentials represent mitigation of 5–80%, and 20–90% of all other agricultural mitigation measures combined, at carbon prices of up to 20, and up to 50 US$/tCO2eq, respectively. Above the level where agricultural products and residues form the sole feedstock, bioenergy competes with other land-uses for available land, water and other resources The mitigation potentials of bioenergy and improved energy efficiency are not included in Table TS.11 or Figure TS.20, as the potential is counted in the user sectors, mainly transport and buildings, respectively (medium agreement, medium evidence) [8.4.4]. The estimates of mitigation potential in the agricultural sector are towards the lower end of the ranges indicated in the Second Assessment Report (SAR) and TAR. This is due mainly to the different time scales considered (2030 here versus 2050 in TAR). In the medium term, much of the mitigation potential is derived from removal of CO2 from the atmosphere and its
conversion to soil carbon, but the magnitude of this process will diminish as soil carbon approaches maximum levels, and longterm mitigation will rely increasingly on reducing emissions of N2O, CH4, and CO2 from energy use, the benefits of which persist indefinitely (high agreement, much evidence) [8.4.3]. Interactions of mitigation options with vulnerability and adaptation Agricultural actions to mitigate GHGs could: a) reduce vulnerability (e.g. if soil carbon sequestration reduces the impacts of drought) or b) increase vulnerability (e.g., if heavy dependence on biomass energy makes energy supply more sensitive to climatic extremes). Policies to encourage mitigation and/or adaptation in agriculture may need to consider these interactions (medium agreement, limited evidence). Similarly, adaptation-driven actions may either a) favour mitigation (e.g., return of residues to fields to improve water-holding capacity will also sequester carbon) or b) hamper mitigation (e.g., use of more nitrogen fertilizer to overcome falling yields, leading to increased N2O emissions). Strategies that simultaneously increase adaptive capacity, reduce vulnerability and mitigate climate change are likely to present fewer adoption barriers than those with conflicting impacts. For example increasing soil organic matter content can both improve fertility and reduce the impact of drought, improving adaptive capacity, making agriculture less vulnerable to climate change, while also sequestering carbon (medium agreement, medium evidence) [8.5]. 65
Technical Summary
Effectiveness of climate policies: opportunities, barriers and implementation issues Actual levels of GHG mitigation practices in the agricultural sector are below the economic potential for the measures reported above (medium agreement, limited evidence). Little progress in implementation has been made because of the costs of implementation and other barriers, including: pressure on agricultural land, demand for agricultural products, competing demands for water as well as various social, institutional and educational barriers (medium agreement, limited evidence). Soil carbon sequestration in European croplands, for instance, is likely to be negligible by 2010, despite significant economic potential. Many of these barriers will not be overcome without policy/economic incentives (medium agreement, limited evidence) [8.6].
Many agricultural mitigation activities show synergy with the goals of sustainability. Mitigation policies that encourage efficient use of fertilizers, maintain soil carbon and sustain agricultural production are likely to have the greatest synergy with sustainable development (high agreement, medium evidence). For example, increasing soil carbon can also improve food security and economic returns. Other mitigation options have less certain impacts on sustainable development. For example, the use of some organic amendments may improve carbon sequestration, but impacts on water quality may vary depending on the amendment. Co-benefits often arise from improved efficiency, reduced cost and environmental co-benefits. Trade-offs relate to competition for land, reduced agricultural productivity and environmental stresses (medium agreement, limited evidence) [8.4.5].
Integrated and non-climate policies affecting emissions of greenhouse gases
Technology research, development, deployment, diffusion and transfer
The adoption of mitigation practices will often be driven largely by goals not directly related to climate change. This leads to varying mitigation responses among regions, and contributes to uncertainty in estimates of future global mitigation potential. Policies most effective at reducing emissions may be those that also achieve other societal goals. Some rural development policies undertaken to fight poverty, such as water management and agro-forestry, are synergistic with mitigation (medium agreement, limited evidence). For example, agro-forestry undertaken to produce fuel wood or to buffer farm incomes against climate variation may also increase carbon sequestration. In many regions, agricultural mitigation options are influenced most by non-climate policies, including macro-economic, agricultural and environmental policies. Such policies may be based on UN conventions (e.g., Biodiversity and Desertification), but are often driven by national or regional issues. Among the most beneficial non-climate policies are those that promote sustainable use of soils, water and other resources in agriculture since these help to increase soil carbon stocks and minimize resource (energy, fertilizer) waste (high agreement, medium evidence) [8.7].
Many of the mitigation strategies outlined for the agriculture sector employ existing technology. For example, reduction in emissions per unit of production will be achieved by increases in crop yields and animal productivity. Such increases in productivity can occur through a wide range of practices − better management, genetically modified crops, improved cultivars, fertilizer-recommendation systems, precision agriculture, improved animal breeds, improved animal nutrition, dietary additives and growth promoters, improved animal fertility, bioenergy feed stocks, anaerobic slurry digestion and CH4 capture systems − all of which reflect existing technology (high agreement, much evidence). Some strategies involve new uses of existing technologies. For example, oils have been used in animal diets for many years to increase dietary energy content, but their role and feasibility as a CH4 suppressant is still new and not fully defined. For some technologies, more research and development will be needed [8.9].
Co-benefits of greenhouse gas mitigation policies Some agricultural practices yield purely ‘win-win’ outcomes, but most involve trade-offs. Agro-ecosystems are inherently complex. The co-benefits and trade-offs of an agricultural practice may vary from place to place because of differences in climate, soil or the way the practice is adopted (high agreement, medium evidence). In producing bioenergy, for example, if the feedstock is crop residues, soil organic matter may be depleted as less carbon is returned, thus reducing soil quality; conversely, if the feedstock is a densely-rooted perennial crop, soil organic matter may be replenished, thereby improving soil quality. 66
Long-term outlook Global food demand may double by 2050, leading to intensified production practices (e.g., increasing use of nitrogen fertilizer). In addition, projected increases in the consumption of livestock products will increase CH4 and N2O emissions if livestock numbers increase, leading to growing emissions in the baseline after 2030. (high agreement, medium evidence). Agricultural mitigation measures will help to reduce GHG emissions per unit of product, relative to the baseline. However, until 2030 only about 10% of the mitigation potential is related to CH4 and N2O. Deployment of new mitigation practices for livestock systems and fertilizer applications will be essential to prevent an increase in emissions from agriculture after 2030. Projecting long-term mitigation potentials is also hampered by other uncertainties. For example, the effects of climate change are unclear: future climate change may reduce soil
Technical Summary
Table TS.12: Estimates of forest area, net changes in forest area (negative numbers indicating decrease), carbon stock in living biomass and growing stock in 1990, 2000 and 2005 [Table 9.1]. Forest area (mill. ha)
Annual change (mill. ha/yr)
Carbon stock in living biomass (MtCO2) 1990
2000
2005
Growing stock in 2005 (million m3)
Region
2005
1990-2000
2000-2005
Africa
635.412
-4.4
-4.0
241267
228067
222933
64957
Asia
571.577
-0.8
1.0
150700
130533
119533
47111
Europe a)
1001.394
0.9
0.7
154000
158033
160967
107264
North and Central America
705.849
-0.3
-0.3
150333
153633
155467
78582
Oceania
206.254
-0.4
-0.4
42533
41800
41800
7361
831.540
-3.8
-4.3
358233
345400
335500
128944
3952.026
-8.9
-7.3
1097067
1057467
1036200
434219
South America World
Note: a) including whole Russian Federation.
carbon-sequestration rates, or could even release soil carbon, though the effect is uncertain as climate change may also increase soil carbon inputs through higher plant production. Some studies have suggested that technological improvements could potentially counteract the negative impacts of climate change on cropland and grassland soil carbon stocks, making technological improvement a key factor in future GHG mitigation. Such technologies could, for example, act through increasing production, thereby increasing carbon returns to the soil and reducing the demand for fresh cropland. (high agreement, medium evidence) [8.10].
9
Forestry
Since the TAR, new mitigation estimates have become available from the local scale to the global scale. Major economic reviews and global assessments have become available. There is early research into the integration of mitigation and adaptation options and the linkages to sustainable development. There is increased attention on reducing emissions from deforestation as a low cost mitigation option, one that will have significant positive side effects. There is some evidence that climate change impacts can also constrain the mitigation potential of forests. Status of the sector, development trends including production and consumption, and implications Global forest cover is 3952 million ha (Table TS.12), about 30% of the world’s land area. Most relevant for the carbon cycle is that between 2000 and 2005 gross deforestation continued at a rate of 12.9 million ha/yr, mainly as a result of converting forests to agricultural land, but also due to expansion of settlements and infrastructure, often for logging. In the 1990s, gross deforestation was slightly higher, 13.1 million ha/yr. Due
to afforestation, landscape restoration and natural expansion of forests, the net loss of forest between 2000 and 2005 was 7.3 million ha/yr, with the largest losses in South America, Africa and Southeast Asia. This net rate of loss was lower than the 8.9 million ha/yr loss in the 1990s (medium agreement, medium evidence) [9.2.1]. Emission sources and sinks; trends On the global scale, during the last decade of the 20th century, deforestation in the tropics and forest regrowth in the temperate zone and parts of the boreal zone remained the major factors responsible for CO2 emissions and removals, respectively (Table TS.12, Figure TS.21). Emissions from deforestation in the 1990s are estimated at 5.8 GtCO2/yr. However, the extent to which the loss of carbon due to tropical deforestation is offset by expanding forest areas and accumulating woody biomass in the boreal and temperate zone is an area of disagreement between actual land observations and estimates using top-down models. The top-down methods based on inversion of atmospheric transport models estimate the net terrestrial carbon sink for the 1990s, the balance of sinks in northern latitudes and sources in the tropics, to be about 9.5 GtCO2. The new estimates are consistent with the increase previously found in the terrestrial carbon sink in the 1990s over the 1980s, but the new sink estimates and the rate of increase may be smaller than previously reported. The residual sink estimate resulting from inversion of atmospheric transport models is significantly higher than any global sink estimate based on land observations. The growing understanding of the complexity of the effects of land-surface change on the climate system shows the importance of considering the role of surface albedo, the fluxes of sensible and latent heat, evaporation and other factors in formulating policy for climate change mitigation in the forest 67
Technical Summary
EECCA
Europe
2000
1995
1900 1995
1900
1855
1995
USA
4000
Non-Annex I South Asia
Latin America and Caribbean
2000
2000
1995
1900
1995
1900
0
1995
0
1855
OECD Pacific 2000 1855
1995
1855
1995 1900
1855
0 -1000
1900
4000
2000
1855
1995
1900
1855
0
0 1900
0
Sub-Saharan Africa 1855
2000
4000
Non-Annex I 2000 East Asia
North Africa 2000 & Middle East 0
1900
1900
0
1855
1995
0
1855
0
Canada
2000
2000
Figure TS.21: Historical forest carbon balance (MtCO2) per region, 1855–2000 [Figure 9.2]. Notes: green = sink. EECCA =Countries of Eastern Europe, the Caucasus and Central Asia. Data averaged per 5-year period; year marks starting year of period.
sector. Complex modelling tools are needed to fully consider the climatic effect of changing land surface and to manage carbon stocks in the biosphere, but are not yet available. The potential effect of projected climate change on the net carbon balance in forests remains uncertain [9.3; 9.4]. As even the current functioning of the biosphere is uncertain, projecting the carbon balance of the global forestry sector remains very difficult. Generally, there is a lack of widely accepted studies and thus a lack of baselines. Trends for development in non-OECD countries, and thus of the deforestation rate, are unclear. In OECD countries and in economies in transition, development of management trends, the wood market, and impacts of climate change remain unclear. Long-term models as reported in Chapter 3, show baseline CO2 emissions from land-use change and forestry in 2030 that are the same or slightly lower than in 2000 (medium agreement, medium evidence) [9.3; 9.4].
• increasing off-site carbon stocks in wood products and enhancing product and fuel substitution. Each mitigation activity has a characteristic time sequence of actions, carbon benefits and costs (Figure TS.22). Relative to a baseline, the largest short-term gains are always achieved through mitigation activities aimed at avoiding emissions (reduced deforestation or degradation, fire protection, slash burning, etc.).
Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability Terrestrial carbon dynamics are characterized by long periods of small rates of carbon uptake per hectare, interrupted by short periods of rapid and large releases of carbon during disturbances or harvest. While individual stands in a forest may be sources or sinks, the carbon balance of the forest is determined by the sum of the net balance of all stands. Options available to reduce emissions by sources and/or increase removals by sinks in the forest sector are grouped into four general categories: • maintaining or increasing the forest area; • maintaining or increasing the site-level carbon density; • maintaining or increasing the landscape-level carbon density and
68
Figure TS.22: Generalized summary of the options available in the forest sector and their type and timing of effects on carbon stocks and the timing of costs [Figure 9.4].
Technical Summary
All forest-management activities aimed at increasing site-level and landscape-level carbon density are common practices that are technically feasible, but the extent and area over which they can be implemented could be increased considerably. Economic considerations are typically the main constraint, because retaining additional carbon on site delays revenues from harvest. In the long term, a sustainable forest-management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual yield of timber, fibre or energy from the forest, will generate the largest sustained mitigation benefit. Regional modelling assessments Bottom-up regional studies show that forestry mitigation options have the economic potential (at costs up to 100 US$/ tCO2-eq) to contribute 1.3-4.2 MtCO2/yr (average 2.7 GtCO2/ yr) in 2030 excluding bioenergy. About 50% can be achieved at a cost under 20 US$/tCO2 (1.6 GtCO2/yr) with large differences between regions. The combined effects of reduced deforestation and degradation, afforestation, forest management, agroforestry and bioenergy have the potential to increase from the present to 2030 and beyond. This analysis assumes gradual implementation of mitigation activities starting now (medium agreement, medium evidence) [9.4.4].
assumptions). Further research is required to narrow the gap in the estimates of mitigation potential from global and regional assessments (medium agreement, medium evidence) [9.4.3]. The best estimate of the economic mitigation potential for the forestry sector at this stage therefore cannot be more certain than a range between 2.7 and 13.8 GtCO2/yr in 2030, for costs <100 US$/tCO2; for costs <20 US$/tCO2 the range is 1.6 to 5 GtCO2/yr. About 65% of the total mitigation potential (up to 100 US$/tCO2-eq) is located in the tropics and about 50% of the total could be achieved by reducing emissions from deforestation (low agreement, medium evidence). Forestry can also contribute to the provision of bioenergy from forest residues. The potential of bioenergy, however, is counted in the power supply, transportation (biofuels), industry and building sectors (see Chapter 11 for an overview). Based on bottom-up studies of potential biomass supply from forestry, and assuming that all of that will be used (which depends entirely on the cost of forestry biomass compared with other sources) a contribution in the order of 0.4 GtCO2/yr could come from forestry. Global top-down models are starting to provide insight on where and which of the carbon mitigation options can best be allocated on the globe (Figure TS.24).
Global top-down models predict mitigation potentials of 13.8 GtCO2-eq/yr in 2030 at carbon prices less than or equal to 100 US$/tCO2. The sum of regional predictions is 22% of this value for the same year. Regional studies tend to use more detailed data and consider a wider range of mitigation options, and thus may more accurately reflect regional circumstances and constraints than simpler, more aggregated global models. However, regional studies vary in model structure, coverage, analytical approach and assumptions (including baseline
3.500
Mt CO2-eq top down
3.000
bottom up 2.500
Agriculture
Ice
Ext. grassland
Tundra
C-Plantations
Grass/Steppe
Bio-energy
Forest
Desert
2.000 1.500 1.000 500
nn
-A
N
on
C
en
tra
la
nd Am So ex er uth O I S ica EC ou D th N As or ia th Am er ic N a on -A A nn fri ca ex IE as tA si EI a T co un tri es Eu ro O pe EC D Pa ci fic M id dl e Ea st
0
Figure TS.23: Comparison of outcomes of economic mitigation potential at <100 US$/tCO2-eq in 2030 in the forestry sector, as based on top-down global models versus the regional modelling results [Figure 9.13].
Figure TS.24: Allocation of global afforestation activities as given by two global top-down models. Top: location of bioenergy and carbon plantations in the world in 2100; bottom: percentage of a grid cell afforested in 2100 [Figure 9.11]. 69
Technical Summary
Interactions of mitigation options with vulnerability and adaptation Mitigation activities for forestry can be designed to be compatible with adapting to climate change, maintaining biodiversity and promoting sustainable development. Comparing environmental and social co-benefits and costs with the carbon benefit will highlight trade-offs and synergies and help promote sustainable development. The literature on the interaction between forestry mitigation and climate change is in its infancy. Forests are likely to be impacted by climate change, which could reduce their mitigation potential. A primary management adaptation option is to reduce as many ancillary stresses on the forest as possible. Maintaining widely dispersed and viable populations of individual species minimizes the probability of localized catastrophic events causing species extinction. Formation of protected areas or nature reserves is an example of mitigation as well as adaptation. Protecting areas (with corridors) also leads to conservation of biodiversity, in turn reducing vulnerability to climate change. Forestry-mitigation projects provide adaptation co-benefits for other sectors. Examples include agro-forestry reducing the vulnerability to drought of rain-fed crop income, mangroves reducing the vulnerability of coastal settlements, and shelter belts slowing desertification (medium agreement, medium evidence) [9.5]. Effectiveness of and experience with climate policies, potentials, barriers and opportunities/ implementation issues Forestry can make a very significant contribution to a low cost global mitigation portfolio that provides synergies with adaptation and sustainable development. Chapter 9 of this report identifies a whole set of options and policies to achieve this mitigation potential. However, this opportunity has so far not been taken because of the current institutional context, lack of incentives for forest managers and lack of enforcement of existing regulations. Without better policy instruments, only a small portion of this potential is likely to be realized. Realization of the mitigation potential requires institutional capacity, investment capital, technology, R&D and transfer, as well as appropriate (international) policies and incentives. In many regions, their absence has been a barrier to implementation of forestry-mitigation activities. Notable exceptions exist, however, such as regional successes in reducing deforestation rates and implementing afforestation programmes (high agreement, much evidence). Multiple and location-specific strategies are required to guide mitigation policies in the sector. The optimum choices depend on the current state of the forests, the dominant drivers of forest change, and the anticipated future dynamics of the forests within each region. Participation of all stakeholders and policy-makers 70
is necessary to promote mitigation projects and design an optimal mix of measures. Integration of mitigation in the forestry sector into land-use planning could be important in this respect. Most existing policies to slow tropical deforestation have had minimal impact due to lack of regulatory and institutional capacity or countervailing profitability incentives. In addition to more dedicated enforcement of regulations, well-constructed carbon markets or other environmental service payment schemes may help overcome barriers to reducing deforestation by providing positive financial incentives for retaining forest cover. There have been several proposals to operationalize activities post 2012, including market-based as well as non-market based approaches; for example, through a dedicated fund to voluntarily reduce emissions from deforestation. Policy measures such as subsidies and tax exemptions have been used successfully to encourage afforestation and reforestation both in developed and developing countries. Care must be taken, however, to avoid possible negative environmental and social impacts of largescale plantation establishment. Despite relative low costs and many potential positive side effects of afforestation and reforestation under the Clean Development Mechanism (CDM), not many project activities are yet being implemented due to a number of barriers, including the late agreement on and complexity of the rules governing afforestation and reforestation CDM project activities. The requirements for forestry mitigation projects to become viable on a larger scale include certainty over future commitments, streamlined and simplified rules, and reductions in transaction costs. Standardization of project assessment can play an important role in overcoming uncertainties among potential buyers, investors and project participants (high agreement, medium evidence) [9.6]. Forests and Sustainable Development While the assessment in the forestry chapter identifies remaining uncertainties about the magnitude of the mitigation benefits and costs, the technologies and knowledge required to implement mitigation activities exist today. Forestry can make a significant and sustained contribution to a global mitigation portfolio, while also meeting a wide range of social, economic and ecological objectives. Important co-benefits can be gained by considering forestry mitigation options as an element of broader land-management plans. Plantations can contribute positively, for example, to employment, economic growth, exports, renewable energy supply and poverty alleviation. In some instances, plantations may also lead to negative social impacts such as loss of grazing land and source of traditional livelihoods. Agro-forestry can produce a wide range of economic, social and environmental benefits; probably wider than large-scale afforestation. Since ancillary benefits tend to be local rather than global, identifying
Technical Summary
and accounting for them can reduce or partially compensate the costs of the mitigation measures (high agreement, medium evidence) [9.7]. Technology research, development, deployment, diffusion and transfer The deployment, diffusion and transfer of technologies such as improved forest-management systems, forest practices and processing technologies including bioenergy, are key to improving the economic and social viability of the different mitigation options. Governments could play a critical role in providing targeted financial and technical support, promoting the participation of communities, institutions and NGOs (high agreement, much evidence) [9.8]. Long-term outlook Uncertainties in the carbon cycle, the uncertain impacts of climate change on forests and its many dynamic feedbacks, time-lags in the emission-sequestration processes, as well as uncertainties in future socio-economic paths (e.g., to what extent deforestation can be substantially reduced in the coming decades) cause large variations in future carbon balance projections for forests. Overall, it is expected that in the long-term, mitigation activities will help increase the carbon sink, with the net balance depending on the region. Boreal primary forests will either be small sources or sinks depending on the net effect of enhancement of growth versus a loss of soil organic matter and emissions from increased fires. Temperate forests will probably continue to be net carbon sinks, favoured also by enhanced forest growth due to climate change. In the tropical regions, human-induced land-use changes are expected to continue to drive the dynamics for decades. Beyond 2040, depending very particularly on the effectiveness of policies aimed at reducing forest degradation and deforestation, tropical forests may become net sinks, depending on the influence of climate change. Also, in the medium to long term, commercial bioenergy is expected to become increasingly important. Developing optimum regional strategies for climate change mitigation involving forests will require complex analyses of the trade-offs (synergies and competition) in land-use between forestry and other land-uses, trade-offs between forest conservation for carbon storage and other environmental services such as biodiversity and watershed conservation and sustainable forest harvesting to provide society with carboncontaining fibre, timber and bioenergy resources, and trade-offs among utilization strategies of harvested wood products aimed at maximizing storage in long-lived products, recycling, and use for bioenergy [9.9].
10
Waste management
Status of the sector, development trends and implications Waste generation is related to population, affluence and urbanization. Current global rates of post-consumer waste generation are estimated to be 900-1300 Mt/yr. Rates have been increasing in recent years, especially in developing countries with rapid population growth, economic growth and urbanization. In highly developed countries, a current goal is to decouple waste generation from economic driving forces such as GDP — recent trends suggest that per capita rates of post-consumer waste generation may be peaking as a result of recycling, re-use, waste minimization, and other initiatives (medium agreement, medium evidence) [10.1, 10.2]. Post-consumer waste is a small contributor to global GHG emissions (<5%), with landfill CH4 accounting for >50% of current emissions. Secondary sources of emissions are wastewater CH4 and N2O; in addition, minor emissions of CO2 result from incineration of waste containing fossil carbon. In general, there are large uncertainties with respect to quantification of direct emissions, indirect emissions and mitigation potentials for the waste sector, which could be reduced by consistent and coordinated data collection and analysis at the national level. There are currently no inventory methods for annual quantification of GHG emissions from waste transport, nor for annual emissions of fluorinated gases from post-consumer waste (high agreement, much evidence) [10.3]. It is important to emphasize that post-consumer waste constitutes a significant renewable energy resource that can be exploited through thermal processes (incineration and industrial co-combustion), landfill gas utilization and use of anaerobic digester biogas. Waste has an economic advantage in comparison to many biomass resources because it is regularly collected at public expense. The energy content of waste can be most efficiently exploited using thermal processes: during combustion, energy is obtained directly from biomass (paper products, wood, natural textiles, food) and from fossil carbon sources (plastics, synthetic textiles). Assuming an average heating value of 9 GJ/t, global waste contains >8 EJ of available energy, which could increase to 13 EJ (nearly 2% of primary energy demand) in 2030 (medium agreement, medium evidence) [10.1]. Currently, more than 130 million tonnes/yr of waste are combusted worldwide, which is equivalent to >1 EJ/yr. The recovery of landfill CH4 as a source of renewable energy was commercialized more than 30 years ago with a current energy value of >0.2 EJ/yr. Along with thermal processes, landfill gas and anaerobic digester gas can provide important local sources of supplemental energy (high agreement, much evidence) [10.1, 10.3].
71
Technical Summary
Because of landfill gas recovery and complementary measures (increased recycling and decreased landfilling through the implementation of alternative technologies), emissions of CH4 from landfills in developed countries have been largely stabilized. Choices for mature, large-scale waste management technologies to avoid or reduce GHG emissions compared with landfilling include incineration for waste-to-energy and biological processes such as composting or mechanicalbiological treatment (MBT). However, in developing countries, landfill CH4 emissions are increasing as more controlled (anaerobic) landfilling practices are being implemented. This is especially true for rapidly urbanizing areas where engineered landfills provide a more environmentally acceptable wastedisposal strategy than open dumpsites by reducing disease vectors, toxic odours, uncontrolled combustion and pollutant emissions to air, water and soil. Paradoxically, higher GHG emissions occur as the aerobic production of CO2 (by burning and aerobic decomposition) is shifted to anaerobic production of CH4. To a large extent, this is the same transition to sanitary landfilling that occurred in many developed countries during 1950–1970. The increased CH4 emissions can be mitigated by accelerating the introduction of engineered gas recovery, aided by Kyoto mechanisms such as CDM and Joint Implementation (JI). As of late October 2006, landfill gas recovery projects accounted for 12% of the average annual Certified Emission Reductions (CERs) under CDM. In addition, alternative waste management strategies such as recycling and composting can be implemented in developing countries. Composting can provide an affordable, sustainable alternative to engineered landfills, especially where more labour-intensive, lower-technology strategies are applied to selected biodegradable waste streams (high agreement, medium evidence) [10.3]. Recycling, re-use and waste minimization initiatives, both public and private, are indirectly reducing GHG emissions by decreasing the mass of waste requiring disposal. Depending on regulations, policies, markets, economic priorities and local constraints, developed countries are implementing increasingly higher recycling rates to conserve resources, offset fossil fuel use, and avoid GHG generation. Quantification of global recycling rates is not currently possible because of varying baselines and definitions; however, local reductions of >50% have been achieved. Recycling could be expanded practically in many countries to achieve additional reductions. In developing countries, waste scavenging and informal recycling are common practices. Through various diversion and small-scale recycling activities, those who make their living from decentralized waste management can significantly reduce the mass of waste that requires more centralized solutions. Studies indicate that lowtechnology recycling activities can also generate significant employment through creative microfinance and other smallscale investments. The challenge is to provide safer, healthier working conditions than currently experienced by waste scavengers at uncontrolled dumpsites (medium agreement, medium evidence) [10.3].
72
For wastewater, only about 60% of the global population has sanitation coverage (sewerage). For wastewater treatment, almost 90% of the population in developed countries but less than 30% in developing countries has improved sanitation (including sewerage and waste water treatment, septic tanks, or latrines). In addition to GHG mitigation, improved sanitation and wastewater management provide a wide range of health and environmental co-benefits (high agreement, much evidence) [10.2, 10.3]. With respect to both waste and wastewater management in developing countries, two key constraints to sustainable development are the lack of financial resources and the selection of appropriate and truly sustainable technologies for a particular setting. It is a significant and costly challenge to implementing waste and wastewater collection, transport, recycling, treatment and residuals management in many developing countries. However, the implementation of sustainable waste and wastewater infrastructure yields multiple co-benefits to assist with the implementation of Millennium Development Goals (MDGs) via improved public health, conservation of water resources, and reduction of untreated discharges to air, surface water, groundwater, soils and coastal zones (high agreement, much evidence) [10.4]. Emission trends With total 2005 emissions of approximately 1300 MtCO2eq/yr, the waste sector contributes about 2–3% of total GHG emissions from Annex I and EIT countries and 4–5% from nonAnnex I countries (see Table TS.13). For 2005–2020, businessas-usual (BAU) projections indicate that landfill CH4 will remain the largest source at 55–60% of the total. Landfill CH4 emissions are stabilizing and decreasing in many developed countries as a result of increased landfill gas recovery combined with waste diversion from landfills through recycling, waste minimization and alternative thermal and biological waste management strategies. However, landfill CH4 emissions are increasing in developing countries because of larger quantities of municipal solid waste from rising urban populations, increasing economic development and, to some extent, the replacement of open burning and dumping by engineered landfills. Without additional measures, a 50% increase in landfill CH4 emissions from 2005 to 2020 is projected, mainly from the Non-Annex I countries. Wastewater emissions of CH4 and N2O from developing countries are also rising rapidly with increasing urbanization and population. Moreover, because the wastewater emissions in Table TS.13 are based on human sewage only and are not available for all developing countries, these emissions are underestimated (high agreement, medium evidence) [10.1, 10.2, 10.3, 10.4].
Technical Summary
Table TS.13: Trends for GHG emissions from waste using 1996 and 2006 UNFCCC inventory guidelines, extrapolations and BAU projections (MtCO2-eq, rounded) [Table 10.3]. Source
1990
1995
2000
2005
2010
2015
2020
Landfill CH4
550
585
590
635
700
795
910
Wastewatera CH4
450
490
520
590
600
630
670
1996 guidelines
Wastewatera N2O
80
90
90
100
100
100
100
1996 guidelines
Incineration CO2
40
40
50
50
50
60
60
2006 guidelines
1120
1205
1250
1375
1450
1585
1740
Total
Notes Averaged using 1996/2006 guidelines
Note: a) wastewater emissions are underestimated - see text.
Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability Existing waste management technologies can effectively mitigate GHG emissions from this sector – a wide range of mature, low- to high-technology, environmentallyeffective strategies are commercially available to mitigate emissions and provide co-benefits for improved public health and safety, soil protection, pollution prevention and local energy supply. Collectively, these technologies can directly reduce GHG emissions (through landfill CH4 recovery and utilization, improved landfill practices, engineered wastewater management, utilization of anaerobic digester biogas) or avoid significant GHG generation (through controlled composting of organic waste, state-of-the-art incineration, expanded sanitation coverage). In addition, waste minimization, recycling and reuse represent an important and increasing potential for indirect reduction of GHG emissions through the conservation of raw materials, improved energy and resource efficiency and fossil fuel avoidance. For developing countries, environmentally responsible waste management at an appropriate level of technology promotes sustainable development and improves public health (high agreement, much evidence) [10.4]. Because waste management decisions are often made locally without concurrent quantification of GHG mitigation, the importance of the waste sector for reducing global GHG emissions has been underestimated (high agreement, medium evidence) [10.1; 10.4]. Flexible strategies and financial incentives can expand waste management options to achieve GHG mitigation goals – in the context of integrated waste management, local technology decisions are a function of many competing variables, including waste quantity and characteristics, cost and financing issues, regulatory constraints and infrastructure requirements, including available land area and collection/ transportation considerations. Life-cycle assessment (LCA) can provide decision-support tools (high agreement, much evidence) [10.4]. Landfill CH4 emissions are directly reduced through engineered gas extraction and recovery systems consisting
of vertical wells and/or horizontal collectors. In addition, landfill gas offsets the use of fossil fuels for industrial or commercial process heating, onsite generation of electricity or as a feedstock for synthetic natural gas fuels. Commercial recovery of landfill CH4 has occurred at full scale since 1975 with documented utilization in 2003 at 1150 plants recovering 105 MtCO2–eq/yr. Because there are also many projects that flare gas without utilization, the total recovery is likely to be at least double this figure (high agreement, medium evidence) [10.1; 10.4]. A linear regression using historical data from the early 1980s to 2003 indicates a growth rate for landfill CH4 utilization of approximately 5% per year. In addition to landfill gas recovery, the further development and implementation of landfill ‘biocovers’ can provide an additional low cost, biological strategy to mitigate emissions since landfill CH4 (and non-methane volatile organic compounds (NMVOCs)) emissions are also reduced by aerobic microbial oxidation in landfill-cover soils (high agreement, much evidence) [10.4]. Incineration and industrial co-combustion for waste-to-energy provide significant renewable energy benefits and fossil fuel offsets at >600 plants worldwide, while producing very minor GHG emissions compared with landfilling. Thermal processes with advanced emission controls are a proven technology but more costly than controlled landfilling with landfill gas recovery (high agreement, medium evidence) [10.4]. Controlled biological processes can also provide important GHG mitigation strategies, preferably using source-separated waste streams. Aerobic composting of waste avoids GHG generation and is an appropriate strategy for many developed and developing countries, either as a stand-alone process or as part of mechanicalbiological treatment. In many developing countries, notably China and India, small-scale low-technology anaerobic digestion has also been practised for decades. Since higher-technology incineration and composting plants have proved unsustainable in a number of developing countries, lower-technology composting or anaerobic digestion can be implemented to provide sustainable waste management solutions (high agreement, medium evidence) [10.4]. For 2030, the total economic reduction potential for CH4 emissions from landfilled waste at costs of <20 US$/tCO2-eq 73
Technical Summary
Table TS.14: Ranges for economic mitigation potential for regional landfill CH4 emissions at various cost categories in 2030, see notes [Table 10.5]. Economic mitigation potential (MtCO2-eq) at various cost categories (US$/tCO2-eq)
Region
Projected emissions in 2030 (MtCO2-eq)
Total economic mitigation potential at <100 US$/tCO2-eq (MtCO2-eq)
<0
0-20
20-50
50-100
OECD
360
100-200
100-120
20-100
0-7
1
EIT
180
100
30-60
20-80
5
1-10
Non-OECD
960
200-700
200-300
30-100
0-200
0-70
1500
400-1000
300-500
70-300
5-200
10-70
Global
Notes: 1) Costs and potentials for wastewater mitigation are not available. 2) Regional numbers are rounded to reflect the uncertainty in the estimates and may not equal global totals. 3) Landfill carbon sequestration not considered. 4) The timing of measures limiting landfill disposal affects the annual mitigation potential in 2030. The upper limits assume that landfill disposal is limited in the coming years to 15% of the waste generated globally. The lower limits reflect a more realistic timing for implementation of measures reducing landfill disposal.
ranges between 400 and 800 MtCO2-eq. Of this total, 300– 500 MtCO2-eq/yr has negative cost (Table TS.14). For the long term, if energy prices continue to increase, there will be more profound changes in waste management strategies related to energy and materials recovery in both developed and developing countries. Thermal processes, which have higher unit costs than landfilling, become more viable as energy prices increase. Because landfills continue to produce CH4 for many decades, both thermal and biological processes are complementary to increased landfill gas recovery over shorter time frames (high agreement, limited evidence) [10.4]. For wastewater, increased levels of improved sanitation in developing countries can provide multiple benefits for GHG mitigation, improved public health, conservation of water resources and reduction of untreated discharges to water and soils. Historically, urban sanitation in developed countries has focused on centralized sewerage and wastewater treatment plants, which are too expensive for rural areas with low population density and may not be practical to implement in rapidly growing, peri-urban areas with high population density. It has been demonstrated that a combination of low cost technology with concentrated efforts for community acceptance, participation and management can successfully expand sanitation coverage. Wastewater is also a secondary water resource in countries with water shortages where water re-use and recyling could assist many developing and developed countries with irregular water supplies. These measures also encourage smaller wastewater treatment plants with reduced nutrient loads and proportionally lower GHG emissions. Estimates of global or regional mitigation costs and potentials for wastewater are not currently available (high agreement, limited evidence) [10.4].
74
Effectiveness of and experience with climate policies, potentials, barriers and opportunities/ implementation issues Because landfill CH4 is the dominant GHG from this sector, a major strategy is the implementation of standards that encourage or mandate landfill CH4 recovery. In developed countries, landfill CH4 recovery has increased as a result of direct regulations requiring landfill gas capture, voluntary measures including GHG-emissions credits trading and financial incentives (including tax credits) for renewable energy or green power. In developing countries, it is anticipated that landfill CH4 recovery will increase during the next two decades as controlled landfilling is phased in as a major waste disposal strategy. JI and the CDM have already proved to be useful mechanisms for external investment from industrialized countries, especially for landfill gas recovery projects where the lack of financing is a major impediment. The benefits are twofold: reduced GHG emissions with energy benefits from landfill CH4 plus upgraded landfill design and operations. Currently (late October 2006), under the CDM, the annual average CERs for the 33 landfill gas recovery projects constitute about 12% of the total. Most of these projects (Figure TS.25) are located in Latin-American countries (72% of landfill gas CERs), dominated by Brazil (9 projects; 48% of CERs) (high agreement, medium evidence) [10.4]. In the EU, landfill gas recovery is mandated at existing sites, while the landfilling of organic waste is being phased out via the landfill directive (1999/31/EC). This directive requires, by 2016, a 65% reduction relative to 1995 in the mass of biodegradable organic waste that is landfilled annually. As a result, post-consumer waste is being diverted to incineration and to mechanical and biological treatment (MBT) before landfilling to recover recyclables and reduce the organic carbon content. In 2002, EU waste-to-energy plants generated about 40 million GJ of electrical and 110 million GJ of thermal energy, while between 1990 and 2002, landfill CH4 emissions in the EU decreased by
Technical Summary
Costa Rica El Salvador 1% 2% Projects <100,000 CER/yr Tunesia 3% 3% Mexico 3% China 6% Chile 7% Brazil 48% Argentina 11%
Armenia 16% Figure TS.25: Distribution of landfill gas CDM projects based on average annual CERs for registered projects late October, 2006 [Figure 10.9]. Note: Includes 11 MtCO2-eq/yr CERs for landfill CH4 out of 91 MtCO2-eq/yr total. Projects <100,000 CERs/yr are located in Israel, Bolivia, Bangladesh and Malaysia.
almost 30% due to the landfill directive and related national legislation (high agreement, much evidence) [10.4, 10.5]. Integrated and non-climate policies affecting emissions of greenhouse gases: GHG mitigation as the co-benefit of waste policies and regulations; role of sustainable development GHG mitigation is often not the primary driver, but is itself a co-benefit of policies and measures in the waste sector that address broad environmental objectives, encourage energy recovery from waste, reduce use of virgin materials, restrict choices for ultimate waste disposal, promote waste recycling and re-use and encourage waste minimization. Policies and measures to promote waste minimization, re-use and recycling indirectly reduce GHG emissions from waste. These measures include Extended Producer Responsibility (EPR), unit pricing (or PAYT/‘Pay As You Throw’) and landfill taxes. Other measures include separate and efficient collection of recyclables together with both unit pricing and landfill tax systems. Some Asian countries are encouraging ‘circular economy’ or ‘sound material-cycle society’ as a new development strategy whose core concept is the circular (closed) flow of materials and the use of raw materials and energy through multiple phases. Because of limited data, differing baselines and other regional conditions, it is not currently possible to quantify the global effectiveness of these strategies in reducing GHG emissions (medium agreement, medium evidence) [10.5]. In many countries, waste and wastewater management policies are closely integrated with environmental policies
and regulations pertaining to air, water and soil quality as well as to renewable energy initiatives. Renewable-energy programmes include requirements for electricity generation from renewable sources, mandates for utilities to purchase power from small renewable providers, renewable energy tax credits, and green power initiatives, which allow consumers to choose renewable providers. In general, the decentralization of electricity generation capacity via renewables can provide strong incentives for electrical generation from landfill CH4 and thermal processes for waste-to-energy (high agreement, much evidence) [10.5]. Although policy instruments in the waste sector consist mainly of regulations, there are also economic measures in a number of countries to encourage particular waste management technologies, recycling and waste minimization. These include incinerator subsidies or tax exemptions for waste-to-energy. Thermal processes can most efficiently exploit the energy value of post-consumer waste, but must include emission controls to limit emissions of secondary air pollutants. Subsidies for the construction of incinerators have been implemented in several countries, usually combined with standards for energy efficiency. Tax exemptions for electricity generated by waste incinerators and for waste disposal with energy recovery have also been adopted (high agreement, much evidence) [10.5]. The co-benefits of effective and sustainable waste and wastewater collection, transport, recycling, treatment and disposal include GHG mitigation, improved public health, conservation of water resources and reductions in the discharge of untreated pollutants to air, soil, surface water and groundwater. Because there are many examples of abandoned waste and wastewater plants in developing countries, it must be stressed that a key aspect of sustainable development is the selection of appropriate technologies that can be sustained within the specific local infrastructure (high agreement, medium evidence) [10.5]. Technology research, development and diffusion In general, the waste sector is characterized by mature technologies that require further diffusion in developing countries. Advances under development include: • Landfilling: Implementation of optimized gas collection systems at an early stage of landfill development to increase long-term gas collection efficiency. Optimization of landfill biodegradation (bioreactors) to provide greater process control and shorter waste degradation lifetimes. Construction of landfill ‘biocovers’ that optimize microbial oxidation of CH4 and NMVOCs to minimize emissions. • Biological processes: For developing countries, lowertechnology, affordable sustainable composting and anaerobic digestion strategies for source-separated biodegradable waste. • Thermal processes: Advanced waste-to-energy technologies that can provide higher thermal and electrical efficiencies 75
Technical Summary
than current incinerators (10–20% net electrical efficiency). Increased implementation of industrial co-combustion using feedstocks from various waste fractions to offset fossil fuels. Gasification and pyrolysis of source-separated waste fractions in combination with improved, lower-cost separation technologies for production of fuels and feedstocks. • Recycling, re-use, waste minimization, pre-treatment (improved mechanical-biological treatment processes) Innovations in recycling technology and process improvements resulting in decreased use of virgin materials, energy conservation, and fossil fuel offsets. Development of innovative but lowtechnology recycling solutions for developing countries. • Wastewater: New low-technology ecological designs for improved sanitation at the household and small community level, which can be implemented sustainably for efficient small-scale wastewater treatment and water conservation in both developed and developing countries (high agreement, limited evidence) [10.5; 10.6]. Long-term outlook, systems transitions To minimize future GHG emissions from the waste sector, it is important to preserve local options for a wide range of integrated and sustainable management strategies. Furthermore, primary reductions in waste generation through recycling, reuse, and waste minimization can provide substantial benefits for the conservation of raw materials and energy. Over the long term, because landfills continue to produce CH4 for decades, landfill gas recovery will be required at existing landfills even as many countries change to non-landfilling technologies such as incineration, industrial co-combustion, mechanical-biological treatment, large-scale composting and anaerobic digestion. In addition, the ‘back-up’ landfill will continue to be a critical component of municipal solid waste planning. In developing countries, investment in improved waste and wastewater management confers significant co-benefits for public health and safety, environmental protection and infrastructure development.
11
Mitigation from a cross-sectoral perspective
Mitigation options across sectors While many of the technological, behavioural and policy options mentioned in Chapters 4–10 concern specific sectors, some technologies and policies reach across many sectors; for example, the use of biomass and the switch from highcarbon fuels to gas affect energy supply, transport, industry and buildings. Apart from potentials for common technologies, these examples also highlight possible competition for resources, such as finance and R&D support [11.2.1]. The bottom-up compilation of mitigation potentials by sector is complicated by interactions and spill-overs between 76
sectors, over time and over regions and markets. A series of formal procedures has been used to remove potential double counting, such as reduction of the capacity needed in the power sector due to electricity saving in industry and the buildings sector. An integration of sector potentials in this way is required to summarize the sectoral assessments of Chapters 4–10. The uncertainty of the outcome is influenced by issues of comparability of sector calculations, difference in coverage between the sectors (e.g., the transport sector) and the aggregation itself, in which only the main and direct sector interactions have been taken into account [11.3.1]. The top-down estimates were derived from stabilization scenarios, i.e., runs towards long-term stabilization of atmospheric GHG concentration [3.6]. Figure TS.26A and Table TS.15 show that the bottom-up assessments emphasize the opportunities for no-regrets options in many sectors, with a bottom-up estimate for all sectors by 2030 of about 6 GtCO2-eq at negative costs; that is, net benefits. A large share of the no-regrets options is in the building sector. The total for bottom-up low cost options (no-regrets and other options costing less than 20 US$/tCO2-eq) is around 13 GtCO2eq (ranges are discussed below). There are additional bottomup potentials of around 6 and 4 GtCO2-eq at additional costs of <50 and 100 US$/tCO2-eq respectively (medium agreement, medium evidence) [11.3.1]. There are several qualifications to these estimates in addition to those mentioned above. First, in the bottom-up estimates a set of emission-reduction options, mainly for co-generation, parts of the transport sector and non-technical options such as behavioural changes, are excluded because the available literature did not allow a reliable assessment. It is estimated that the bottom-up potentials are therefore underestimated by 10–15%. Second, the chapters identify a number of key sensitivities that have not been quantified, relating to energy prices, discount rates and the scaling-up of regional results for the agricultural and forestry options. Third, there is a lack of estimates for many EIT countries and substantial parts of the non-OECD/EIT region [11.3.1]. The estimates of potentials at carbon prices <20 US$/tCO2eq are lower than the TAR bottom-up estimates that were evaluated for carbon prices <27 US$/tCO2-eq, due to better information in recent literature (high agreement, much evidence). Figure TS.15 and Table TS.16 show that the overall bottom-up potentials are comparable with those of the 2030 results from top-down models, as reported in Chapter 3. At the sectoral level, there are larger differences between bottom-up and top-down, mainly because the sector definitions in top-down models often differ from those in bottom-up assessments (table TS.17). Although there are slight differences
Technical Summary
35
GtCO2-eq
35
30
30
25
25
20
20
15
15
10
10
5
5
0
GtCO2-eq
0
low end of range
<0
<20
high end of range
<50
low end of range
<100 US$/tCO2-eq
<20
<50
high end of range
<100 US$/tCO2-eq
Figure TS.26A: Global economic mitigation potential in 2030 estimated from bottom-up studies. Data from Table TS.15. [Figure 11.3].
Figure TS.26B: Global economic mitigation potential in 2030 estimated from top-down studies. Data from Table TS.16. [Figure 11.3].
between the baselines assumed for top-down and bottom-up assessments, the results are close enough to provide a robust estimate of the overall economic mitigation potential by 2030. The mitigation potential at carbon prices of <100 US$/tCO2-eq is about 25–50% of 2030 baseline emissions (high agreement, much evidence).
supply sector. However, for an end-use sector analysis as used for the results in Figure TS.27, the highest potential lies in the building and agriculture sectors. For agriculture and forestry, top-down estimates are lower than those from bottom-up studies. This is because these sectors are generally not well covered in top-down models. The energy supply and industry estimates from top-down models are generally higher than those from bottom-up assessments (high agreement, medium evidence) [11.3.1].
Table TS.17 shows that for point-of-emission analysis18 a large part of the long-term mitigation potential is in the energy-
Table TS.15: Global economic mitigation potential in 2030 estimated from bottom-up studies [11.3].
Carbon price (US$/tCO2-eq)
Economic potential (GtCO2-eq/yr)
Reduction relative to SRES A1 B (68 GtCO2-eq/yr) (%)
Reduction relative to SRES B2 (49 GtCO2-eq/yr) (%)
0
5-7
7-10
10-14
20
9-17
14-25
19-35
50
13-26
20-38
27-52
100
16-31
23-46
32-63
Reduction relative to SRES A1 B (68 GtCO2-eq/yr) (%)
Reduction relative to SRES B2 (49 GtCO2-eq/yr) (%)
Table TS.16: Global economic mitigation potential in 2030 estimated from top-down studies [11.3].
Carbon price (US$/tCO2-eq)
Economic potential (GtCO2-eq/yr)
20
9-18
13-27
18-37
50
14-23
21-34
29-47
100
17-26
25-38
35-53
18 In a point-of-emission analysis, emissions from electricity use are allocated to the energy-supply sector. In an end-use sector analysis, emissions from electricity are allocated to the respective end-use sector (particularly relevant for industry and buildings).
77
Technical Summary
Table TS.17: Economic potential for sectoral mitigation by 2030: comparison of bottom-up (from Table 11.3) and top-down estimates (from Section 3.6) [Table 11.5]. Economy-wide model (‘topdown’) snapshot of mitigation by 2030 (GtCO2-eq/yr)
Sector-based (‘bottom-up’) potential by 2030 (GtCO2-eq/yr) Sectors
End-use sector allocation (allocation of electricity savings to end-use sectors)
Point-of-emissions allocation (emission reductions from end-use electricity savings allocated to energy supply sector) Carbon price <20 US$/tCO2-eq
Chapter of report
Low
High
Low
High
Low
4
Energy supply & conversion
1.2
2.4
4.4
6.4
3.9
High 9.7
5
Transport
1.3
2.1
1.3
2.1
0.1
1.6
6
Buildings
4.9
6.1
1.9
2.3
0.3
1.1
7
Industry
0.7
1.5
0.5
1.3
1.2
3.2
8
Agriculture
0.3
2.4
0.3
2.4
0..6
1.2
9
Forestry
0.6
1.9
0.6
1.9
0.2
0.8
10
Waste
0.3
0.8
0.3
0.8
0.7
0.9
11
Total
9.3
17.1
9.1
17.9
8.7
17.9
Carbon price <50 US$/tCO2-eq 4
Energy supply & conversion
2.2
4.2
5.6
8.4
6.7
12.4
5
Transport
1.5
2.3
1.5
2.3
0.5
1.9
6
Buildings
4.9
6.1
1.9
2.3
0.4
1.3
7
Industry
2.2
4.7
1.6
4.5
2.2
4.3
8
Agriculture
1.4
3.9
1.4
3.9
0.8
1.4
9
Forestry
1.0
3.2
1.0
3.2
0.2
0.8
10
Waste
11
Total
4
0.4
1.0
0.4
1.0
0.8
1.0
13.3
25.7
13.2
25.8
13.7
22.6
Energy supply & conversion
2.4
4.7
6.3
9.3
8.7
14.5
5
Transport
1.6
2.5
1.6
2.5
0.8
2.5
6
Buildings
5.4
6.7
2.3
2.9
0.6
1.5
7
Industry
2.5
5.5
1.7
4.7
3.0
5.0
8
Agriculture
2.3
6.4
2.3
6.4
0.9
1.5
Carbon price <100 US$/tCO2-eq
9
Forestry
1.3
4.2
1.3
4.2
0.2
0.8
10
Waste
0.4
1.0
0.4
1.0
0.9
1.1
11
Total
15.8
31.1
15.8
31.1
16.8
26.2
Sources: Tables 3.16, 3.17 and 11.3 See notes to Tables 3.16, 3.17 and 11.3, and Annex 11.1.
Bioenergy options are important for many sectors by 2030, with substantial growth potential beyond, although no complete integrated studies are available for supply-demand balances. Key preconditions for such contributions are the development of biomass capacity (energy crops) in balance with investments in agricultural practices, logistic capacity and markets, together with commercialization of second-generation biofuel production. Sustainable biomass production and use 78
could ensure that issues in relation to competition for land and food, water resources, biodiversity and socio-economic impacts are not creating obstacles (high agreement, limited evidence) [11.3.1.4]. Apart from the mitigation options mentioned in the sectoral Chapters 4–10, geo-engineering solutions to the enhanced greenhouse effect have been proposed. However, options
Technical Summary
7
GtCO2-eq/yr
6 5 4 3 2
Non-OECD/EIT EIT OECD World total
1
Energy supply
Transport
Buildings
Agriculture
Forestry
0 <1 0
<5 0
0 <2
<5 0 <1 00
<2 0
0
Industry
<5 0 <1 00
<2
00 <1
<5 0
<2 0
<5 0 <1 00
<2 0
0
00 <1
<5
<2 0
00
0 <5
<1
<2
0
0
US$/tCO2-eq
Waste
Figure TS.27: Estimated sectoral economic potential for global mitigation for different regions as a function of carbon price in 2030 from bottom-up studies, compared to the respective baselines assumed in the sector assessments. A full explanation of the derivation of this figure is found in Section 11.3. Notes: 1. The ranges for global economic potentials as assessed in each sector are shown by vertical lines. The ranges are based on end-use allocations of emissions, meaning that emissions of electricity use are counted towards the end-use sectors and not to the energy supply sector. 2. The estimated potentials have been constrained by the availability of studies particularly at high carbon price levels. 3. Sectors used different baselines. For industry the SRES B2 baseline was taken, for energy supply and transport the WEO 2004 baseline was used; the building sector is based on a baseline in between SRES B2 and A1B; for waste, SRES A1B driving forces were used to construct a waste specific baseline, agriculture and forestry used baselines that mostly used B2 driving forces. 4. Only global totals for transport are shown because international aviation is included [5.4]. 5. Categories excluded are: non-CO2 emissions in buildings and transport, part of material efficiency options, heat production and cogeneration in energy supply, heavy duty vehicles, shipping and high-occupancy passenger transport, most high-cost options for buildings, wastewater treatment, emission reduction from coal mines and gas pipelines, fluorinated gases from energy supply and transport. The underestimation of the total economic potential from these emissions is of the order of 10-15%.
to remove CO2 directly from the air, for example, by iron fertilization of the oceans, or to block sunlight, remain largely speculative and may have a risk of unknown side effects. Blocking sunlight does not affect the expected escalation in atmospheric CO2 levels, but could reduce or eliminate the associated warming. This disconnection of the link between CO2 concentration and global temperature could have beneficial consequences, for example, in increasing the productivity of agriculture and forestry (in as far as CO2 fertilization is effective), but they do not mitigate or address other impacts such as further acidification of the oceans. Detailed cost estimates for these options have not been published and they are without a clear institutional framework for implementation (medium agreement, limited evidence) [11.2.2]. Mitigation costs across sectors and macro-economic costs The costs of implementing the Kyoto Protocol are estimated to be much lower than the TAR estimates due to US rejection of the Protocol. With full use of the Kyoto flexible mechanisms, costs are estimated at less than 0.05% of Annex B (without US) GDP (TAR Annex B: 0.1–1.1%). Without flexible mechanisms,
19
costs are now estimated at less than 0.1% (TAR 0.2–2%) (high agreement, much evidence) [11.4]. Modelling studies of post-2012 mitigation have been assessed in relation to their global effects on CO2 abatement by 2030, the carbon prices required and their effects on GDP or GNP (for the long-term effects of stabilization after 2030 see Chapter 3). For Category IV19 pathways (stabilization around 650 ppm CO2-eq) with CO2 abatement less than 20% below baseline and up to 25 US$/tCO2 carbon prices, studies suggest that gross world product would be, at worst, some 0.7% below baseline by 2030, consistent with the median of 0.2% and the 10–90 percentile range of –0.6 to 1.2% for the full set of scenarios given in Chapter 3. Effects are more uncertain for the more stringent Category III pathways (stabilization around 550 ppm CO2-eq) with CO2 abatement less than 40% and up to 50 US$/tCO2 carbon prices, with most studies suggesting costs less than 1% of global gross world product, consistent with the median of 0.6% and the 10–90 percentile range of 0 to 2.5% for the full set in Chapter 3. Again, the estimates are heavily dependent on approaches and assumptions. The few studies with baselines that require
See Chapter 3 for the definition of Category III and IV pathways.
79
Technical Summary
higher CO2 reductions to achieve the targets require higher carbon prices and most report higher GDP costs. For category I and II studies (stabilization between 445 and 535 ppm CO2eq) costs are less than 3% GDP loss, but the number of studies is relatively small and they generally use low baselines. The lower estimates of the studies assessed here, compared with the full set of studies reported in Chapter 3, are caused mainly by a larger share of studies that allow for enhanced technological innovation triggered by policies, particularly for more stringent mitigation scenarios (high agreement, medium evidence) [11.4]. All approaches indicate that no single sector or technology will be able to address the mitigation challenge successfully on its own, suggesting the need for a diversified portfolio based on a variety of criteria. Top-down assessments agree with the bottom-up results in suggesting that carbon prices around 2050 US$/tCO2-eq (73-183 US$/tC-eq) are sufficient to drive large-scale fuel-switching and make both CCS and low-carbon power sources economic as technologies mature. Incentives of this order might also play an important role in avoiding deforestation. The various short- and long-term models come up with differing estimates, the variation of which can be explained mainly by approaches and assumptions regarding the use of revenues from carbon taxes or permits, treatment of technological change, degree of substitutability between internationally traded products, and the disaggregation of product and regional markets (high agreement, much evidence) [11.4, 11.5, 11.6]. The development of the carbon price and the corresponding emission reductions will determine the level at which atmospheric GHG concentrations can be stabilized. Models suggest that a predictable and ongoing gradual increase in the carbon price that would reach 20–50 $US/tCO2-eq by 2020– 2030 corresponds with Category III stabilization (550 ppm CO2-eq). For Category IV (650 ppm CO2-eq), such a price level could be reached after 2030. For stabilization at levels between 450 and 550 ppm CO2-eq, carbon prices of up to 100 US$/tCO2-eq need to be reached by around 2030 (medium agreement, medium evidence) [11.4, 11.5, 11.6]. In all cases, short-term pathways towards lower stabilization levels, particularly for Category III and below, would require many additional measures around energy efficiency, lowcarbon energy supply, other mitigation actions and avoidance of investment in very long-lived carbon-intensive capital stock. Studies of decision-making under uncertainty emphasize the need for stronger early action, particularly on long-lived infrastructure and other capital stock. Energy sector infrastructure (including power stations) alone is projected to require at least US$ 20 trillion investment to 2030 and the options for stabilization will be heavily constrained by the nature and carbon intensity of this investment. Initial estimates for lower carbon scenarios show a large redirection of investment, with net additional investments ranging from negligible to less than 5% (high agreement, much evidence) [11.6]. 80
As regards portfolio analysis of government actions, a general finding is that a portfolio of options that attempts to balance emission reductions across sectors in a manner that appears equitable (e.g., by equal percentage reduction), is likely to be more costly than an approach primarily guided by cost-effectiveness. Portfolios of energy options across sectors that include low-carbon technologies will reduce risks and costs, because fossil fuel prices are expected to be more volatile relative to the costs of alternatives, in addition to the usual benefits from diversification. A second general finding is that costs will be reduced if options that correct the two market failures of climate change damages and technological innovation benefits are combined, for example, by recycling revenues from permit auctions to support energy-efficiency and low-carbon innovations (high agreement, medium evidence) [11.4]. Technological change across sectors A major development since the TAR has been the inclusion in many top-down models of endogenous technological change. Using different approaches, modelling studies suggest that allowing for endogenous technological change may lead to substantial reductions in carbon prices as well as GDP costs, compared with most of the models in use at the time of the TAR (when technological change was assumed to be included in the baseline and largely independent of mitigation policies and action). Studies without induced technological change show that carbon prices rising to 20 to 80 US$/tCO2-eq by 2030 and 30 to 155 US$/tCO2-eq by 2050 are consistent with stabilization at around 550 ppm CO2-eq by 2100. For the same stabilization level, studies since TAR that take into account induced technological change lower these price ranges to 5 to 65 US$/tCO2eq in 2030 and 15 to 130 US$/tCO2-eq in 2050. The degree to which costs are reduced hinges critically on the assumptions about the returns from climate change mitigation R&D expenditures, spill-overs between sectors and regions, crowding-out of other R&D, and, in models including learningby-doing, learning rates (high agreement, much evidence) [11.5]. Major technological shifts like carbon capture and storage, advanced renewables, advanced nuclear and hydrogen require a long transition as learning-by-doing accumulates and markets expand. Improvement of end-use efficiency therefore offers more important opportunities in the short term. This is illustrated by the relatively high share of the buildings and industry sector in the 2030 potentials (Table TS.17). Other options and sectors may play a more significant role in the second half of the century (see Chapter 3) (high agreement, much evidence) [11.6]. Spill-over effects from mitigation in Annex I countries on Non-Annex I countries Spill-over effects of mitigation from a cross-sectoral perspective are the effects of mitigation policies and measures in one country or group of countries on sectors in other countries. One aspect of spill-over is so-called ‘carbon leakage’:
Technical Summary
the increase in CO2 emissions outside the countries taking domestic measures divided by the emission reductions within these countries. The simple indicator of carbon leakage does not cover the complexity and range of effects, which include changes in the pattern and magnitude of global emissions. Modelling studies provide wide-ranging outcomes on carbon leakages depending on their assumptions regarding returns to scale, behaviour in the energy-intensive industry, trade elasticities and other factors. As in the TAR, the estimates of carbon leakage from implementation of the Kyoto Protocol are generally in the range of 5–20% by 2010. Empirical studies on the energy-intensive industries with exemptions under the EU Emission Trading Scheme (ETS) highlight that transport costs, local market conditions, product variety and incomplete information favour local production, and conclude that carbon leakage is unlikely to be substantial (medium agreement, medium evidence) [11.7]. Effects of existing mitigation actions on competitiveness have been studied. The empirical evidence seems to indicate that losses of competitiveness in countries implementing Kyoto are not significant, confirming a finding in the TAR. The potential beneficial effect of technology transfer to developing countries arising from technological development brought about by Annex I action may be substantial for energy-intensive industries, but has not so far been quantified in a reliable manner (medium agreement, low evidence) [11.7]. Perhaps one of the most important ways in which spill-overs from mitigation actions in one region affect others is through the effect on world fossil fuel prices. When a region reduces its fossil fuel demand because of mitigation policy, it will reduce the world demand for that commodity and so put downward pressure on the prices. Depending on the response of the fossil fuel producers, oil, gas or coal prices may fall, leading to loss of revenues by the producers, and lower costs of imports for the consumers. As in the TAR, nearly all modelling studies that have been reviewed show more pronounced adverse effects on oil-producing countries than on most Annex I countries that are taking the abatement measures. Oil-price protection strategies may limit income losses in the oil-producing countries (high agreement, limited evidence) [11.7].
In addition, the benefits of avoided emissions of air pollutants have been estimated for agricultural production and the impact of acid precipitation on natural ecosystems. Such near-term benefits provide the basis for a no-regrets GHG-reduction policy, in which substantial advantages accrue even if the impact of human-induced climate change turns out to be less than current projections show. Including co-benefits other than those for human health and agricultural productivity (e.g., increased energy security and employment) would further enhance the cost savings (high agreement, limited evidence) [11.8]. A wealth of new literature has pointed out that addressing climate change and air pollution simultaneously through a single set of measures and policies offers potentially large reductions in the costs of air-pollution control. An integrated approach is needed to address those pollutants and processes for which trade-offs exist. This is, for instance, the case for NOx controls for vehicles and nitric acid plants, which may increase N2O emissions, or the increased use of energy-efficient diesel vehicles, which emit relatively more fine particulate matter than their gasoline equivalents (high agreement, much evidence) [11.8]. Adaptation and mitigation There can be synergies or trade-offs between policy options that can support adaptation and mitigation. The synergy potential is high for biomass energy options, land-use management and other land-management approaches. Synergies between mitigation and adaptation could provide a unique contribution to rural development, particularly in least-developed countries: many actions focusing on sustainable natural resource management could provide both significant adaptation benefits and mitigation benefits, mostly in the form of carbon sequestration. However, in other cases there may be trade-offs, such as the growth of energy crops that may affect food supply and forestry cover, thereby increasing vulnerability to the impacts of climate change (medium agreement, limited evidence) [11.9].
12
Sustainable development and mitigation
Co-benefits of mitigation Many recent studies have demonstrated significant benefits of carbon-mitigation strategies on human health, mainly because they also reduce other airborne emissions, for example, SO2, NOx and particulate matter. This is projected to result in the prevention of tens of thousands of premature deaths in Asian and Latin American countries annually, and several thousands in Europe. However, monetization of mortality risks remains controversial, and hence a large range of benefit estimates can be found in the literature. However, all studies agree that the monetized health benefits may offset a substantial fraction of the mitigation costs (high agreement, much evidence) [11.8].
Relationship between sustainable development and climate change mitigation The concept of sustainable development was adopted by the World Commission on Environment and Development and there is agreement that sustainable development involves a comprehensive and integrated approach to economic, social and environmental processes. Discussions on sustainable development, however, have focused primarily on the environmental and economic dimensions. The importance of social, political and cultural factors is only now getting more recognition. Integration is essential in order to articulate 81
Technical Summary
development trajectories that are sustainable, including addressing the climate change problem [12.1]. Although still in the early stages, there is growing use of indicators to measure and manage the sustainability of development at the macro and sectoral levels, which is driven in part by the increasing emphasis on accountability in the context of governance and strategy initiatives. At the sectoral level, progress towards sustainable development is beginning to be measured and reported by industry and governments using, inter alia, green certification, monitoring tools or emissions registries. Review of the indicators shows, however, that few macro-indicators include measures of progress with respect to climate change (high agreement, much evidence) [12.1.3]. Climate change is influenced not only by the climate-specific policies that are put in place (the ‘climate first approach’), but also by the mix of development choices that are made and the development trajectories that these policies lead to (the ‘development first approach’) - a point reinforced by global scenario analysis published since the TAR. Making development more sustainable by changing development paths can thus make a significant contribution to climate goals. It is important to note, however, that changing development pathways is not about choosing a mappedout path, but rather about navigating through an uncharted and evolving landscape (high agreement, much evidence) [12.1.1]. It has further been argued that sustainable development might decrease the vulnerability of all countries, and particularly of developing countries, to climate change impacts. Framing the debate as a development problem rather than an environmental one may better address the immediate goals of all countries, particularly developing countries and their special vulnerability to climate change, while at the same time addressing the driving forces for emissions that are linked to the underlying development path [12.1.2]. Making development more sustainable Decision-making on sustainable development and climate change mitigation is no longer solely the purview of governments. The literature recognizes the shift to a more inclusive concept of governance, which includes the contributions of various levels of government, the private sector, non-governmental actors and civil society. The more that climate change issues are mainstreamed as part of the planning perspective at the appropriate level of implementation, and the more all these relevant parties are involved in the decision-making process in a meaningful way, the more likely are they to achieve the desired goals (high agreement, medium evidence) [12.2.1]. Regarding governments, a substantial body of political theory identifies and explains the existence of national policy styles or political cultures. The underlying assumption of this work is that individual countries tend to process problems in a specific manner, regardless of the distinctiveness or 82
specific features of any specific problem; a national ‘way of doing things’. Furthermore, the choice of policy instruments is affected by the institutional capacity of governments to implement the instrument. This implies that the preferred mix of policy decisions and their effectiveness in terms of sustainable development and climate change mitigation depend strongly on national characteristics (high agreement, much evidence). However, our understanding of which types of policies will work best in countries with particular national characteristics remains sketchy [12.2.3]. The private sector is a central player in ecological and sustainability stewardship. Over the past 25 years, there has been a progressive increase in the number of companies that are taking steps to address sustainability issues at either the firm or industry level. Although there has been progress, the private sector has the capacity to play a much greater role in making development more sustainable if awareness that this will probably benefit its performance grows (medium agreement, medium evidence) [12.2.3]. Citizen groups play a significant role in stimulating sustainable development and are critical actors in implementing sustainable development policy. Apart from implementing sustainable development projects themselves, they can push for policy reform by awareness-raising, advocacy and agitation. They can also pull policy action by filling the gaps and providing policy services, including in the areas of policy innovation, monitoring and research. Interactions can take the form of partnerships or be through stakeholder dialogues that can provide citizens’ groups with a lever for increasing pressure on both governments and industry (high agreement, medium evidence) [12.2.3]. Deliberative public-private partnerships work most effectively when investors, local governments and citizen groups are willing to work together to implement new technologies, and provide arenas to discuss such technologies that are locally inclusive (high agreement, medium evidence) [12.2.3]. Implications of development choices for climate change mitigation In a heterogeneous world, an understanding of different regional conditions and priorities is essential for mainstreaming climate change policies into sustainable-development strategies. Region- and country-specific case studies demonstrate that different development paths and policies can achieve notable emissions reductions, depending on the capacity to realize sustainability and climate change objectives [12.3]. In industrialized countries, climate change continues to be regarded mainly as a separate, environmental problem to be addressed through specific climate change policies. A fundamental and broad discussion in society on the implications of development pathways for climate change in general and climate change mitigation in particular in the industrialized
Technical Summary
countries has not been seriously initiated. Priority mitigation areas for countries in this group may be in energy efficiency, renewable energy, CCS, etc. However, low-emission pathways apply not only to energy choices. In some regions, land-use development, particularly infrastructure expansion, is identified as a key variable determining future GHG emissions [12.2.1; 12.3.1]. Economies in transition as a single group no longer exist. Nevertheless, Central and Eastern Europe and the countries of Eastern Europe, the Caucasus and Central Asia (EECCA) do share some common features in socio-economic development and in climate change mitigation and sustainable development. Measures to decouple economic and emission growth would be especially important for this group [12.2.1; 12.3.1]. Some large developing countries are projected to increase their emissions at a faster rate than the industrialized world and the rest of developing nations as they are in the stage of rapid industrialization. For these countries, climate change mitigation and sustainable-development policies can complement one another; however, additional financial and technological resources would enhance their capacity to pursue a low-carbon path of development [12.2.1; 12.3.1]. For most other developing countries, adaptive and mitigative capacities are low and development aid can help to reduce their vulnerability to climate change. It can also help to reduce their emissions growth while addressing energy-security and energyaccess problems. CDM can provide financial resources for such developments. Members of the Organization of the PetroleumExporting Countries (OPEC) are unique in the sense that they may be adversely affected by development paths that reduce the demand for fossil fuels. Diversification of their economies is high on their agenda [12.2.1; 12.3.1]. Some general conclusions emerge from the case studies reviewed in this chapter on how changes in development pathways at the sectoral level have (or could) lower emissions (high agreement, medium evidence) [12.2.4]: • GHG emissions are influenced by, but not rigidly linked to, economic growth: policy choices can make a difference. • Sectors where effective production is far below the maximum feasible production with the same amount of inputs – that is, sectors that are far from their production frontier – have opportunities to adopt ‘win-win-win’ policies, that is, policies that free up resources and bolster growth, meet other sustainable-development goals and also reduce GHG emissions relative to baseline. • Sectors where production is close to the optimal given available inputs – i.e., sectors that are closer to the production frontier – also have opportunities to reduce emissions by meeting other sustainable development goals. However, the closer one gets to the production frontier, the more tradeoffs are likely to appear.
• What matters is not only that a ‘good’ choice is made at a certain point in time, but also that the initial policy is sustained for a long time – sometimes several decades – to really have effects. • It is often not one policy decision, but an array of decisions that are needed to influence emissions. This raises the issue of coordination between policies in several sectors and at various scales. Mainstreaming requires that non-climate policies, programmes and/or individual actions take climate change mitigation into consideration, in both developing and developed countries. However, merely piggybacking climate change on to an existing political agenda is unlikely to succeed. The ease or difficulty with which mainstreaming is accomplished will depend on both mitigation technologies or practices, and the underlying development path. Weighing other development benefits against climate benefits will be a key basis for choosing development sectors for mainstreaming. Decisions about macro-economic policy, agricultural policy, multilateral development bank lending, insurance practices, electricity market reform, energy security, and forest conservation, for example, which are often treated as being apart from climate policy, can have profound impacts on emissions, the extent of mitigation required, and the costs and benefits that result. However, in some cases, such as shifting from biomass cooking to liquid petroleum gas (LPG) in rural areas in developing countries, it may be rational to disregard climate change considerations because of the small increase in emissions when compared with its development benefits (see Table TS.18) (high agreement, medium evidence) [12.2.4]. In general terms, there is a high level of agreement on the qualitative findings in this chapter about the linkages between mitigation and sustainable development: the two are linked, and synergies and trade-offs can be identified. However, the literature about the links and more particularly, about how these links can be put into action in order to capture synergies and avoid trade-offs, is as yet sparse. The same applies to good practice guidance for integrating climate change considerations into relevant non-climate policies, including analysis of the roles of different actors. Elaborating possible development paths that nations and regions can pursue – beyond more narrowly conceived GHG emissions scenarios or scenarios that ignore climate change – can provide the context for new analysis of the links, but may require new methodological tools (high agreement, limited evidence) [12.2.4]. Implications of mitigation choices for sustainable development trajectories There is a growing understanding of the opportunities to choose mitigation options and their implementation in such a way that there will be no conflict with or even benefits for other dimensions of sustainable development; or, where trade-offs are inevitable, to allow rational choices to be made. A summary of 83
Technical Summary
Table TS.18: Mainstreaming climate change into development choices – selected examples [Table 12.3].
Selected sectors
Non-climate policy instruments and actions that are candidates for mainstreaming
Primary decisionmakers and actors
Global GHG emissions by sector that could be addressed by non-climate policies (% of global GHG emissions)a, d
Comments
Macro economy
Implement non-climate taxes/ subsidies and/or other fiscal and regulatory policies that promote SD
State (governments at all levels)
100
Total global GHG emissions
Combination of economic, regulatory, and infrastructure non-climate policies could be used to address total global emissions.
Forestry
Adoption of forest conservation and sustainable management practices
State (governments at all levels) and civil society (NGOs)
7
GHG emissions from deforestation
Legislation/regulations to halt deforestation, improve forest management, and provide alternative livelihoods can reduce GHG emissions and provide other environmental benefits.
Electricity
Adoption of cost-effective renewables, demand-side management programmes, and reduction of transmission and distribution losses
State (regulatory commissions), market (utility companies) and, civil society (NGOs, consumer groups)
20b
Electricity sector CO2 emissions (excluding auto producers)
Rising share of GHG-intensive electricity generation is a global concern that can be addressed through non-climate policies.
Petroleum imports
Diversifying imported and domestic fuel mix and reducing economy’s energy intensity to improve energy security
State and market (fossil fuel industry)
20b
CO2 emissions associated with global crude oil and product imports
Diversification of energy sources to address oil security concerns could be achieved such that GHG emissions are not increased.
Rural energy in developing countries
Policies to promote rural LPG, kerosene and electricity for cooking
State and market (utilities and petroleum companies), civil society (NGOs)
<2c
GHG emissions from biomass fuel use, not including aerosols
Biomass used for rural cooking causes health impacts due to indoor air pollution, and releases aerosols that add to global warming. Displacing all biomass used for rural cooking in developing countries with LPG would emit 0.70 GtCO2eq., a relatively modest amount compared with 2004 total global GHG emissions.
Insurance for building and transport sectors
Differentiated premiums, liability insurance exclusions, improved terms for green products
State and market (insurance companies)
20
Transport and building sector GHG emissions
Escalating damages due to climate change are a source of concern to insurance industry. Insurance industry could address these through the types of policies noted here.
International finance
Country and sector strategies and project lending that reduces emissions
State (international) financial institutions) and market (commercial banks)
25b
CO2 emissions from developing countries (non-Annex I)
International financial institutions can adopt practices so that loans for GHG-intensive projects in developing countries that lock-in future emissions are avoided.
Notes: a) Data from Chapter 1 unless noted otherwise. b) CO2 emissions from fossil fuel combustion only; IEA (2006). c) CO2 emissions only. Authors estimate, see text. d) Emissions indicate the relative importance of sectors in 2004. Sectoral emissions are not mutually exclusive, may overlap, and hence sum up to more than total global emissions, which are shown in the Macro economy row.
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Technical Summary
Table TS.19: Sectoral mitigation options and sustainable development (economic, local environmental and social) considerations: synergies and trade-offs [Table 12.4]. Sector and mitigation options
Potential SD synergies and conditions for implementation
Potential SD trade-offs
Energy supply and use: Chapters 4-7 Energy efficiency improvement in all sectors (buildings, transportation, industry, and energy supply) (Chapters 4-7)
- Almost always cost-effective, reduces or eliminates local pollutant emissions and consequent health impacts, improves indoor comfort and reduces indoor noise levels, creates business opportunities and jobs and improves energy security - Government and industry programmes can help overcome lack of information and principal agent problems - Programmes can be implemented at all levels of government and industry - Important to ensure that low-income household energy needs are given due consideration, and that the process and consequences of implementing mitigation options are, or the result is, gender-neutral
- Indoor air pollution and health impacts of improving the thermal efficiency of biomass cooking stoves in developing country rural areas are uncertain
Fuel switching and other options in the transportation and buildings sectors (Chapters 5 and 6)
- CO2 reduction costs may be offset by increased health benefits - Promotion of public transport and non-motorized transport has large and consistent social benefits - Switching from solid fuels to modern fuels for cooking and heating indoors can reduce indoor air pollution and increase free time for women in developing countries - Institutionalizing planning systems for CO2 reduction through coordination between national and local governments is important for drawing up common strategies for sustainable transportation systems
- Diesel engines are generally more fuel-efficient than gasoline engines and thus have lower CO2 emissions, but increase particle emissions. - Other measures (CNG buses, hybrid dieselelectric buses and taxi renovation) may provide little climate benefit.
Replacing imported fossil fuels with domestic alternative energy sources (DAES) (Chapter 4)
- Important to ensure that DAES is cost-effective - Reduces local air pollutant emissions. - Can create new indigenous industries (e.g., Brazil ethanol programme) and hence generate employment
- Balance of trade improvement is traded off against increased capital required for investment - Fossil fuel-exporting countries may face reduced exports - Hydropower plants may displace local populations and cause environmental damage to water bodies and biodiversity
Replacing domestic fossil fuel with imported alternative energy sources (IAES) (Chapter 4)
-
Almost always reduces local pollutant emissions Implementation may be more rapid than DAES Important to ensure that IAES is cost-effective Economies and societies of energy-exporting countries would benefit
- Could reduce energy security - Balance of trade may worsen but capital needs may decline
Afforestation
- Can reduce wasteland, arrest soil degradation, and manage water runoff - Can retain soil carbon stocks if soil disturbance at planting and harvesting is minimized - Can be implemented as agroforestry plantations that enhance food production - Can generate rural employment and create rural industry - Clear delineation of property rights would expedite implementation of forestation programmes
- Use of scarce land could compete with agricultural land and diminish food security while increasing food costs - Monoculture plantations can reduce biodiversity and are more vulnerable to disease - Conversion of floodplain and wetland could hamper ecological functions
Avoided deforestation
- Can retain biodiversity, water and soil management benefits, and local rainfall patterns - Reduce local haze and air pollution from forest fires - If suitably managed, it can bring revenue from ecotourism and from sustainably harvested timber sales - Successful implementation requires involving local dwellers in land management and/or providing them alternative livelihoods, enforcing laws to prevent migrants from encroaching on forest land.
- Can result in loss of economic welfare for certain stakeholders in forest exploitation (land owners, migrant workers) - Reduced timber supply may lead to reduced timber exports and increased use of GHGintensive construction materials - Can result in deforestation with consequent SD implications elsewhere
Forest Management
- See afforestation
- Fertilizer application can increase N2O production and nitrate runoff degrading local (ground)water quality - Prevention of fires and pests has short term benefits but can increase fuel stock for later fires unless managed properly
Forestry sector: Chapter 9
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Technical Summary
Table TS.19. Continued. Sector and mitigation options
Potential SD synergies and conditions for implementation
Potential SD trade-offs
- Mostly positive when practised with crop residues (shells, husks, bagasse and/or tree trimmings). - Creates rural employment. - Planting crops/trees exclusively for bio-energy requires that adequate agricultural land and labour is available to avoid competition with food production
- Can have negative environmental consequences if practised unsustainably - biodiversity loss, water resource competition, increased use of fertilizer and pesticides. - Potential problem with food security (locationspecific) and increased food costs.
Cropland management (management of nutrients, tillage, residues, and agroforestry; water, rice, and set-aside)
- Improved nutrient management can improve groundwater quality and environmental health of the cultivated ecosystem
- Changes in water policies could lead to clash of interests and threaten social cohesiveness - Could lead to water overuse
Grazing land management
- Improves livestock productivity, reduces desertification, and provide social security for the poor - Requires laws and enforcement to ban free grazing
Livestock management
- Mix of traditional rice cultivation and livestock management would enhance incomes even in semiarid and arid regions
Bio-energy (chapter 8 en 9) Bio-energy production
Agriculture: Chapter 8
Waste management: Chapter 10 Engineered sanitary landfilling with landfill gas recovery to capture methane gas
- Can eliminate uncontrolled dumping and open burning of waste, improving health and safety for workers and residents. - Sites can provide local energy benefits and public spaces for recreation and other social purposes within the urban infrastructure.
- When done unsustainably can cause leaching that leads to soil and groundwater contamination with potentially negative health impacts
Biological - Can destroy pathogens and provide useful soil processes for waste and amendments if properly implemented using sourcewastewater (composting, separated organic waste or collected wastewater. anaerobic digestion, aerobic - Can generate employment and anaerobic wastewater - Anaerobic processes can provide energy benefits processes) from CH4 recovery and use.
- A source of odours and water pollution if not properly controlled and monitored.
Incineration and other thermal processes
- Obtain the most energy benefit from waste.
- Expensive relative to controlled landfilling and composting. - Unsustainable in developing countries if technical infrastructure not present. - Additional investment for air pollution controls and source separation needed to prevent emissions of heavy metals and other air toxics.
Recycling, re-use, and waste minimization
- Provide local employment as well as reductions in energy and raw materials for recycled products. - Can be aided by NGO efforts, private capital for recycling industries, enforcement of environmental regulations, and urban planning to segregate waste treatment and disposal activities from community life.
- Uncontrolled waste scavenging results in severe health and safety problems for those who make their living from waste - Development of local recycling industries requires capital.
Note: Material in this table is drawn from the Chapters 4–11. Where new material is introduced, it is referenced in the accompanying text below, which describes the SD implications of mitigation options in each sector.
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Technical Summary
the sustainable development implications of the main climate change mitigation options is given in Table TS.19 [12.3].
National policy instruments, their implementation and interactions
The sustainable development benefits of mitigation options vary within a sector and between regions (high agreement, much evidence): • Generally, mitigation options that improve the productivity of resource use, whether energy, water, or land, yield positive benefits across all three dimensions of sustainable development. Other categories of mitigation options have a more uncertain impact and depend on the wider socio-economic context within which the option is being implemented. • Climate-related policies such as energy efficiency and renewable energy are often economically beneficial, improve energy security and reduce local pollutant emissions. Many energy-supply mitigation options can be designed to also achieve sustainable development benefits such as avoided displacement of local populations, job creation and health benefits. • Reducing deforestation can have significant biodiversity, soil and water conservation benefits, but may result in a loss of economic welfare for some stakeholders. Appropriately designed forestation and bioenergy plantations can lead to restoration of degraded land, manage water runoff, retain soil carbon and benefit rural economies, but may compete with land for food production and be negative for biodiversity. • There are good possibilities for reinforcing sustainable development through mitigation actions in most sectors, but particularly in the waste management, transportation and buildings sectors, notably through decreased energy use and reduced pollution [12.3].
The literature continues to reflect that a wide variety of national policies and measures are available to governments to limit or reduce GHG emissions. These include: regulations and standards, taxes and charges, tradable permits, voluntary agreements, phasing out subsidies and providing financial incentives, research and development and information instruments. Other policies, such as those affecting trade, foreign direct investments and social development goals can also affect GHG emissions. In general, climate change policies, if integrated with other government polices, can contribute to sustainable development in both developed and developing countries (see Chapter 12) [13.1].
13
Policies, instruments and co-operative agreements
Introduction This chapter discusses national policy instruments and their implementation, initiatives of the private sector, local governments and non-governmental organizations, and cooperative international agreements. Wherever feasible, national policies and international agreements are discussed in the context of four principle criteria by which they can be evaluated; that is, environmental effectiveness, costeffectiveness, distributional considerations and institutional feasibility. There are a number of additional criteria that could also be explicitly considered, such as effects on competitiveness and administrative costs. Criteria may be applied by governments in making ex-ante choices among instruments and in ex-post evaluation of the performance of instruments [13.1].
Reducing emissions across all sectors and gases requires a portfolio of policies tailored to fit specific national circumstances. While the literature identifies advantages and disadvantages for any given instrument, the above-mentioned criteria are widely used by policy makers to select and evaluate policies.
All instruments can be designed well or poorly, stringent or lax. Instruments need to be adjusted over time and supplemented with a workable system of monitoring and enforcement. Furthermore, instruments may interact with existing institutions and regulations in other sectors of society (high agreement, much evidence) [13.1]. The literature provides a good deal of information to assess how well different instruments meet the above-mentioned criteria (see Table TS.20) [13.2]. Most notably, it suggests that: • Regulatory measures and standards generally provide environmental certainty. They may be preferable when lack of information or other barriers prevent firms and consumers from responding to price signals. Regulatory standards do not generally give polluters incentives to develop new technologies to reduce pollution, but there are a few examples whereby technology innovation has been spurred by regulatory standards. Standards are common practice in the building sector and there is strong innovation. Although relatively few regulatory standards have been adopted solely to reduce GHG emissions, standards have reduced these gases as a co-benefit (high agreement, much evidence) [13.2]. • Taxes and charges (which can be applied to carbon or all GHGs) are given high marks for cost effectiveness since they provide some assurance regarding the marginal cost of pollution control. They cannot guarantee a particular level of emissions, but conceptually taxes can be designed to be environmentally effective. Taxes can be politically difficult to implement and adjust. As with regulations, their environmental effectiveness depends on their stringency. As with nearly all other policy instruments, care is needed to prevent perverse effects (high agreement, much evidence) [13.2]. 87
Technical Summary
Table TS.20: National environmental policy instruments and evaluative criteria [Table 13.1]. Criteria Environmental effectiveness
Cost-effectiveness
Regulations and standards
Emission levels set directly, though subject to exceptions Depends on deferrals and compliance
Depends on design; uniform application often leads to higher overall compliance costs
Depends on level playing field; small/new actors may be disadvantaged
Depends on technical capacity; popular with regulators, in countries with weak functioning markets
Taxes and charges
Depends on ability to set tax at a level that induces behavioural change
Better with broad application; higher administrative costs where institutions are weak
Regressive; can be improved with revenue recycling
Often politically unpopular; may be difficult to enforce with underdeveloped institutions
Tradable permits
Depends on emissions cap, participation and compliance
Decreases with limited participation and fewer sectors
Depends on initial permit allocation, may pose difficulties for small emitters
Requires well-functioning markets and complementary institutions
Voluntary agreements
Depends on programme design, including clear targets, a baseline scenario, third-party involvement in design and review, and monitoring provisions
Depends on flexibility and extent of government incentives, rewards and penalties
Benefits accrue only to participants
Often politically popular; requires significant number of administrative staff
Subsidies and other incentives
Depends on programme design; less certain than regulations/ standards.
Depends on level and programme design; can be market-distorting
Benefits selected participants; possibly some that do not need it
Popular with recipients; potential resistance from vested interests. Can be difficult to phase out
Research and development
Depends on consistent funding, when technologies are developed, and polices for diffusion. May have high benefits in long-term
Depends on programme design and the degree of risk
Initially benefits selected participants, Potentially easy for funds to be misallocated
Requires many separate decisions; Depends on research capacity and longterm funding
Instrument
Meets distributional considerations
Institutional feasibility
Note: Evaluations are predicated on assumptions that instruments are representative of best practice rather than theoretically perfect. This assessment is based primarily on experiences and literature from developed countries, since peer-reviewed articles on the effectiveness of instruments in other countries were limited. Applicability in specific countries, sectors and circumstances – particularly developing countries and economies in transition – may differ greatly. Environmental and cost effectiveness may be enhanced when instruments are strategically combined and adapted to local circumstances.
• Tradable permits are an increasingly popular economic instrument to control conventional pollutants and GHGs at the sectoral, national and international level. The volume of emissions allowed determines the carbon price and the environmental effectiveness of this instrument, while the distribution of allowances has implications for competitiveness. Experience has shown that banking provisions can provide significant temporal flexibility and that compliance provisions must be carefully designed, if a permit system is to be effective (high agreement, much evidence). Uncertainty in the price of emission reductions under a trading system makes it difficult, a priori, to estimate the total cost of meeting reduction targets [13.2]. • Voluntary agreements between industry and governments and information campaigns are politically attractive, raise awareness among stakeholders and have played a role in the evolution of many national policies. The majority of voluntary agreements has not achieved significant emission reductions beyond business-as-usual. However, some 88
recent agreements in a few countries have accelerated the application of best available technology and led to measurable reductions of emissions compared with the baseline (high agreement, much evidence). Success factors include clear targets, a baseline scenario, third-party involvement in design and review, and formal provisions for monitoring [13.2]. • Voluntary actions: Corporations, sub-national governments, NGOs and civil groups are adopting a wide variety of voluntary actions, independent of government authorities, which may limit GHG emissions, stimulate innovative policies and encourage the deployment of new technologies. By themselves, they generally have limited impact at the national or regional level [13.2]. • Financial incentives (subsidies and tax credits) are frequently used by governments to stimulate the diffusion of new, less GHG-emitting technologies. While the economic costs of such programmes are often higher than for the instruments listed above, they are often critical to overcome barriers to the penetration of new technologies (high agreement, much
Technical Summary
evidence). As with other policies, incentive programmes must be carefully designed to avoid perverse market effects. Direct and indirect subsidies for fossil fuel use and agriculture remain common practice in many countries, although those for coal have declined over the past decade in many OECD countries and in some developing countries (See also Chapter 2, 7 and 11) [13.2]. • Government support for research and development is a special type of incentive, which can be an important instrument to ensure that low GHG-emitting technologies will be available in the long-term. However, government funding for many energy-research programmes dropped after the oil crisis in the 1970s and stayed constant, even after the UNFCCC was ratified. Substantial additional investments in, and policies for, R&D are needed to ensure that technologies are ready for commercialization in order to arrive at stabilization of GHGs in the atmosphere (see Chapter 3), along with economic and regulatory instruments to promote their deployment and diffusion (high agreement, much evidence) [13.2.1]. • Information instruments – sometimes called public disclosure requirements – may positively affect environmental quality by allowing consumers to make better-informed choices. There is only limited evidence that the provision of information can achieve emissions reductions, but it can improve the effectiveness of other policies (high agreement, much evidence) [13.2]. Applying an environmentally effective and economically efficient instrument mix requires a good understanding of the environmental issue to be addressed, of the links with other policy areas and the interactions between the different instruments in the mix. In practice, climate-related policies are seldom applied in complete isolation, as they overlap with other national polices relating to the environment, forestry, agriculture, waste management, transport and energy, and in many cases require more than one instrument (high agreement, much evidence) [13.2]. Initiatives of sub-national governments, corporations and non-governmental organizations The preponderance of the literature reviews nationally based governmental instruments, but corporations, local- and regional authorities, NGOs and civil groups can also play a key role and are adopting a wide variety of actions, independent of government authorities, to reduce emissions of GHGs. Corporate actions range from voluntary initiatives to emissions targets and, in a few cases, internal trading systems. The reasons corporations undertake independent actions include the desire to influence or pre-empt government action, to create financial value, and to differentiate a company and its products. Actions by regional, state, provincial and local governments include renewable portfolio standards, energy-efficiency programmes, emission registries and sectoral cap-and-trade mechanisms. These actions are undertaken to influence national policies, address stakeholder concerns, create incentives for new industries, or
create environmental co-benefits. NGOs promote programmes to reduce emissions through public advocacy, litigation and stakeholder dialogue. Many of the above actions may limit GHG emissions, stimulate innovative policies, encourage the deployment of new technologies and spur experimentation with new institutions, but by themselves generally have limited impact. To achieve significant emission reductions, these actions must lead to changes in national policies (high agreement, much evidence) [13.4]. International agreements (climate change agreements and other arrangements) The UNFCCC and its Kyoto Protocol have set a significant precedent as a means of solving a long-term international environmental problem, but are only the first steps towards implementation of an international response strategy to combat climate change. The Kyoto Protocol’s most notable achievements are the stimulation of an array of national policies, the creation of an international carbon market and the establishment of new institutional mechanisms. Its economic impacts on the participating countries are yet to be demonstrated. The CDM, in particular, has created a large project pipeline and mobilized substantial financial resources, but it has faced methodological challenges regarding the determination of baselines and additionality. The protocol has also stimulated the development of emissions trading systems, but a fully global system has not been implemented. The Kyoto Protocol is currently constrained by the modest emission limits and will have a limited effect on atmospheric concentrations. It would be more effective if the first commitment period were to be followed up by measures to achieve deeper reductions and the implementation of policy instruments covering a higher share of global emissions (high agreement, much evidence) [13.3]. Many options are identified in the literature for achieving emission reductions both under and outside the Convention and its Kyoto Protocol, for example: revising the form and stringency of emission targets; expanding the scope of sectoral and sub-national agreements; developing and adopting common policies; enhancing international RD&D technology programmes; implementing development-oriented actions, and expanding financing instruments (high agreement, much evidence). Integrating diverse elements such as international R&D cooperation and cap-and-trade programmes within an agreement is possible, but comparing the efforts made by different countries would be complex and resource-intensive (medium agreement, medium evidence) [13.3]. There is a broad consensus in the literature that a successful agreement will have to be environmentally effective, costeffective, incorporate distributional considerations and equity, and be institutionally feasible (high agreement, much evidence) [13.3].
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Technical Summary
A great deal of new literature is available on potential structures for and the substance of future international agreements. As has been noted in previous IPCC reports, because climate change is a globally common problem, any approach that does not include a larger share of global emissions will be more costly or less environmentally effective. (high agreement, much evidence) (See Chapter 3) [13.3].
the action will be. States participating in the same ‘tier’ would have the same (or broadly similar) types of commitments. Decisions on how to allocate states to tiers can be based on formalized quantitative or qualitative criteria, or be ‘ad hoc’. Under the principle of sovereignty, states may choose the tier into which they are grouped (high agreement, much evidence) [13.3].
Most proposals for future agreements in the literature include a discussion of goals, specific actions, timetables, participation, institutional arrangements, reporting and compliance provisions. Other elements address incentives, non-participation and noncompliance penalties (high agreement, much evidence) [13.3].
An agreement can have static participation or may change over time. In the latter case, states can ‘graduate’ from one tier of commitments to another. Graduation can be linked to passing of quantitative thresholds for certain parameters (or combinations of parameters) that have been predefined in the agreement, such as emissions, cumulative emissions, GDP per capita, relative contribution to temperature increase or other measures of development, such as the human development index (HDI) (high agreement, much evidence) [13.3].
Goals The specification of clear goals is an important element of any climate agreement. They can both provide a common vision about the near-term direction and offer longer-term certainty, which is called for by business. Goal-setting also helps structure commitments and institutions, provides an incentive to stimulate action and helps establish criteria against which to measure the success in implementing measures (high agreement, much evidence) [13.3]. The choice of the long-term ambition significantly influences the necessary short-term action and therefore the design of the international regime. Abatement costs depend on the goal, vary with region and depend on the allocation of emission allowances among regions and the level of participation (high agreement, much evidence) [13.3]. Options for the design of international regimes can incorporate goals for the short, medium and long term. One option is to set a goal for long-term GHG concentrations or a temperature stabilization goal. Such a goal might be based on physical impacts to be avoided or conceptually on the basis of the monetary and non-monetary damages to be avoided. An alternative to agreeing on specific CO2 concentration or temperature levels is an agreement on specific long-term actions such as a technology R&D and diffusion target – for example, ‘eliminating carbon emissions from the energy sector by 2060’. An advantage of such a goal is that it might be linked to specific actions (high agreement, much evidence) [13.3]. Another option would be to adopt a ‘hedging strategy’, defined as a shorter-term goal on global emissions, from which it is still possible to reach a range of desirable long-term goals. Once the short-term goal is reached, decisions on next steps can be made in light of new knowledge and decreased levels of uncertainty (medium agreement, medium evidence) [13.3]. Participation Participation of states in international agreements can vary from very modest to extensive. Actions to be taken by participating countries can be differentiated both in terms of when such action is undertaken, who takes the action and what 90
Some argue that an international agreement needs to include only the major emitters to be effective, since the largest 15 countries (including the EU-25 as one) make up 80% of global GHG emissions. Others assert that those with historical responsibility must act first. Still another view holds that technology development is the critical factor for a global solution to climate change, and thus agreements must specifically target technology development in Annex I countries – which in turn could offset some or all emissions leakage in Non-Annex I countries. Others suggest that a climate regime is not exclusively about mitigation, but also encompasses adaptation – and that a far wider array of countries is vulnerable to climate change and must be included in any agreement (high agreement, much evidence) [13.3]. Regime stringency: linking goals, participation and timing Under most equity interpretations, developed countries as a group would need to reduce their emissions significantly by 2020 (10–40% below 1990 levels) and to still lower levels by 2050 (40–95% below 1990 levels) for low to medium stabilization levels (450–550ppm CO2-eq) (see also Chapter 3). Under most of the regime designs considered for such stabilization levels, developing-country emissions need to deviate below their projected baseline emissions within the next few decades (high agreement, much evidence). For most countries, the choice of the long-term ambition level will be more important than the design of the emission-reduction regime [13.3]. The total global costs are highly dependent on the baseline scenario, marginal abatement cost estimates, the assumed concentration stabilization level (see also Chapters 3 and 11) and the level (size of the coalition) and degree of participation (how and when allowances are allocated). If, for example some major emitting regions do not participate in the reductions immediately, the global costs of the participating regions will be higher if the goal is maintained (see also Chapter 3). Regional abatement costs are dependent on the allocation of emission allowances to regions, particularly the timing. However, the
Technical Summary
assumed stabilization level and baseline scenario are more important in determining regional costs [11.4; 13.3]. Commitments, timetables and actions There is a significant body of new literature that identifies and evaluates a diverse set of options for commitments that could be taken by different groups. The most frequently evaluated type of commitment is the binding absolute emission reduction cap as included in the Kyoto Protocol for Annex I countries. The broad conclusion from the literature is that such regimes provide certainty about future emission levels of the participating countries (assuming caps are met). Many authors propose that caps be reached using a variety of ‘flexibility’ approaches, incorporating multiple GHGs and sectors as well as multiple countries through emission trading and/or projectbased mechanisms (high agreement, much evidence) [13.3]. While a variety of authors propose that absolute caps be applied to all countries in the future, many have raised concerns that the rigidity of such an approach may unreasonably restrict economic growth. While no consensus approach has emerged, the literature provides multiple alternatives to address this problem, including ‘dynamic targets’ (where the obligation evolves over time), and limits on prices (capping the costs of compliance at a given level – which while limiting costs, would also lead to exceeding the environmental target). These options aim at maintaining the advantages of international emissions trading while providing more flexibility in compliance (high agreement, much evidence). However, there is a trade-off between costs and certainty in achieving an emissions level. [13.3] Market mechanisms International market-based approaches can offer a costeffective means of addressing climate change if they incorporate a broad coverage of countries and sectors. So far, only a few domestic emissions-trading systems are in place, the EU ETS being by far the largest effort to establish such a scheme, with over 11,500 plants allocated and authorized to buy and sell allowances (high agreement, high evidence) [13.2]. Although the Clean Development Mechanism is developing rapidly, the total financial flows for technology transfer have so far been limited. Governments, multilateral organizations and private firms have established nearly 6 billion US$ in carbon funds for carbon-reduction projects, mainly through the CDM. Financial flows to developing countries through CDM projects are reaching levels in the order of several billion US$/yr. This is higher than the flows through the Global Environment Facility (GEF), comparable to the energy-oriented development assistance flows, but at least an order of magnitude lower than all foreign direct investment (FDI) flows (high agreement, much evidence) [13.3]. Many have asserted that a key element of a successful climate change agreement will be its ability to stimulate the
development and transfer of technology – without which it may be difficult to achieve emission reductions on a significant scale. Transfer of technology to developing countries depends mainly on investments. Creating enabling conditions for investments and technology uptake and international technology agreements are important. One mechanism for technology transfer is to establish innovative ways of mobilizing investments to cover the incremental cost of mitigating and adapting to climate change. International technology agreements could strengthen the knowledge infrastructure (high agreement, much evidence) [13.3]. A number of researchers have suggested that sectoral approaches may provide an appropriate framework for postKyoto agreements. Under such a system, specified targets could be set, starting with particular sectors or industries that are particularly important, politically easier to address, globally homogeneous or relatively insulated from competition with other sectors. Sectoral agreement may provide an additional degree of policy flexibility and make comparing efforts within a sector between countries easier, but may be less cost-effective, since trading within a single sector will be inherently more costly than trading across all sectors (high agreement, much evidence) [13.3]. Coordination/harmonization of policies Coordinated policies and measures could be an alternative to or complement internationally agreed targets for emission reductions. A number of policies have been discussed in the literature that would achieve this goal, including taxes (such as carbon or energy taxes); trade coordination/liberalization; R&D; sectoral policies and policies that modify foreign direct investment. Under one proposal, all participating nations – industrialized and developing alike – would tax their domestic carbon usage at a common rate, thereby achieving cost-effectiveness. Others note that while an equal carbon price across countries is economically efficient, it may not be politically feasible in the context of existing tax distortions (high agreement, much evidence) [13.3]. Non-climate policies and links to sustainable development There is considerable interaction between policies and measures taken at the national and sub-national level with actions taken by the private sector and between climate change mitigation and adaptation policies and policies in other areas. There are a number of non-climate national policies that can have an important influence on GHG emissions (see Chapter 12) (high agreement, much evidence). New research on future international agreements could focus on understanding the interlinkages between climate policies, non-climate policies and sustainable development, and how to accelerate the adoption of existing technology and policy tools [13.3]. An overview of how various approaches to international climate change agreements, as discussed above, perform against the criteria, given in the introduction, is presented in 91
Technical Summary
Table TS.21: Assessment of international agreements on climate changea [Table 13.3]. Environmental effectiveness
Approach
Cost effectiveness
Meets distributional considerations
Institutional feasibility
National emission targets and international emission trading (including offsets)
Depends on participation, and compliance
Decreases with limited participation and reduced gas and sector coverage
Depends on initial allocation
Depends on capacity to prepare inventories and compliance. Defections weaken regime stability
Sectoral agreements
Not all sectors amenable to such agreements, limiting overall effectiveness. Effectiveness depends on whether agreement is binding or non-binding
Lack of trading across sectors increases overall costs, although may be cost-effective within individual sectors. Competitive concerns reduced within each sector
Depends on participation. Within-sector competitiveness concerns alleviated if treated equally at global level
Requires many separate decisions and technical capacity. Each sector may require cross-country institutions to manage agreements
Coordinated policies and measures
Individual measures can be effective; emission levels may be uncertain; success will be a function of compliance
Depends on policy design
Extent of coordination could limit national flexibility; but may increase equity
Depends on number of countries; (easier among smaller groups of countries than at the global level)
Cooperation on Technology RD & Db
Depends on funding, when technologies are developed and policies for diffusion
Varies with degree of R&D risk Cooperation reduces individual national risk
Intellectual property concerns may negate the benefits of cooperation
Requires many separate decisions. Depends on research capacity and long-term funding
Development-oriented actions
Depends on national policies and design to create synergies
Depends on the extent of synergies with other development objectives
Depends on distributional effects of development policies
Depends on priority given to sustainable development in national policies and goals of national institutions
Financial mechanisms
Depends on funding
Depends on country and project type
Depends on project and country selection criteria
Depends on national institutions
Capacity building
Varies over time and depends on critical mass
Depends on programme design
Depends on selection of recipient group
Depends on country and institutional frameworks
a)
b)
The table examines each approach based on its capacity to meet its internal goals – not in relation to achieving a global environmental goal. If such targets are to be achieved, a combination of instruments needs to be adopted. Not all approaches have equivalent evaluation in the literature; evidence for individual elements of the matrix varies. Research, Development and Demonstration
Table TS.21. Future international agreements would have stronger support if they meet these criteria (high agreement, much evidence) [13.3].
14
Gaps in knowledge
Gaps in knowledge refer to two aspects of climate change mitigation: • Where additional data collection, modelling and analysis could narrow knowledge gaps, and the resulting improved knowledge and empirical experience could assist decision-making on climate change mitigation measures and policies; to some extent, these gaps are reflected in the uncertainty statements in this report. • Where research and development could improve mitigation technologies and/or reduce their costs. This important aspect is not treated in this section, but is addressed in the chapters where relevant.
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Emission data sets and projections Despite a wide variety of data sources and databases underlying this report, there are still gaps in accurate and reliable emission data by sector and specific processes, especially with regard to non-CO2 GHGs, organic or black carbon, and CO2 from various sources, such as deforestation, decay of biomass and peat fires. Consistent treatment of non-CO2 GHGs in the methodologies underlying scenarios for future GHG emissions is often lacking [Chapters 1 and 3]. Links between climate change and other policies A key innovation of this report is the integrated approach between the assessment of climate change mitigation and wider development choices, such as the impacts of (sustainable) development policies on GHG-emission levels and vice versa. However, there is still a lack of empirical evidence on the magnitude and direction of the interdependence and interaction of sustainable development and climate change, of mitigation and adaptation relationships in relation to development aspects,
Technical Summary
and the equity implications of both. The literature on the linkages between mitigation and sustainable development and, more particularly, on how to capture synergies and minimize tradeoffs, taking into account state, market and civil society’s role, is still sparse. New research is required into the linkages between climate change and national and local policies (including but not limited to energy security, water, health, air pollution, forestry, agriculture) that might lead to politically feasible, economically attractive and environmentally beneficial outcomes. It would also be helpful to elaborate potential development paths that nations and regions can pursue, which would provide links between climate protection and development issues. Inclusion of macro-indicators for sustainable development that can track progress could support such analysis [Chapters 2, 12 and 13]. Studies of costs and potentials The available studies of mitigation potentials and costs differ in their methodological treatment and do not cover all sectors, GHGs or countries. Because of different assumptions, for example, with respect to the baseline and definitions of potentials and costs, their comparability is often limited. Also, the number of studies on mitigation costs, potentials and instruments for countries belonging to Economies in Transition and most developing regions is smaller than for developed and selected (major) developing countries. This report compares costs and mitigation potentials based on bottom-up data from sectoral analyses with top-down costs and potential data from integrated models. The match at the sectoral level is still limited, partly because of lack of or incomplete data from bottom-up studies and differences in sector definitions and baseline assumptions. There is a need for integrated studies that combine top-down and bottom-up elements [Chapters 3, 4, 5, 6, 7, 8, 9 and 10].
Another important gap is the knowledge on spill-over effects (the effects of domestic or sectoral mitigation measures on other countries or sectors). Studies indicate a large range (leakage effects20 from implementation of the Kyoto Protocol of between 5 and 20% by 2010), but are lacking an empirical basis. More empirical studies would be helpful [Chapter 11]. The understanding of future mitigation potentials and costs depends not only on the expected impact of RD&D on technology performance characteristics but also on ‘technology learning’, technology diffusion and transfer which are often not taken into account in mitigation studies. The studies on the influence of technological change on mitigation costs mostly have a weak empirical basis and are often conflicting. Implementation of a mitigation potential may compete with other activities. For instance, the biomass potentials are large, but there may be trade-offs with food production, forestry or nature conservation. The extent to which the biomass potential can be deployed over time is still poorly understood. In general, there is a continued need for a better understanding of how rates of adoption of climate-mitigation technologies are related to national and regional climate and non-climate policies, market mechanisms (investments, changing consumer preferences), human behaviour and technology evolution, change in production systems, trade and finance and institutional arrangements.
20 Carbon leakage is an aspect of spill-overs and is the increase in CO2 emissions outside countries taking domestic measures divided by the emission reductions in these countries.
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1 Introduction Coordinating Lead Authors: H-Holger Rogner (Germany), Dadi Zhou (China)
Lead Authors: Rick Bradley (USA), Philippe Crabbé (Canada), Ottmar Edenhofer (Germany), Bill Hare (Australia), Lambert Kuijpers (The Netherlands), Mitsutsune Yamaguchi (Japan)
Contributing Authors: Nicolas Lefevre (France/USA), Jos Olivier (The Netherlands), Hongwei Yang (China)
Review Editors: Hoesung Lee (Republic of Korea) and Richard Odingo (Kenya)
This chapter should be cited as: Rogner, H.-H., D. Zhou, R. Bradley. P. Crabbé, O. Edenhofer, B.Hare (Australia), L. Kuijpers, M. Yamaguchi, 2007: Introduction. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Introduction
Chapter 1
Table of Contents Executive Summary ................................................... 97 1.1
Introduction ........................................................ 99
1.2
Ultimate objective of the UNFCCC .............. 99
1.3
1.4
1.5
1.2.1
Article 2 of the Convention ................................... 99
1.2.2
What is dangerous interference with the climate system? ................................................................ 99
1.2.3
Issues related to the implementation of Article 2 ............................................................. 100
Energy, emissions and trends in Research and Development – are we on track? ......... 102 1.3.1
Review of the last three decades ....................... 102
1.3.2
Future outlook .................................................... 109
1.3.3
Technology research, development and deployment: needs and trends ......................... 112
Institutional architecture ............................... 112 1.4.1
UNFCCC and its Kyoto Protocol........................ 112
1.4.2
Technology cooperation and transfer ................ 113
Changes from previous assessments and roadmap............................................................. 114 1.5.1
Previous assessments........................................ 114
1.5.2
Roadmap ............................................................ 114
References ................................................................... 115
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Chapter 1
Introduction
EXECUTIVE SUMMARY The ultimate objective of the United Nations Framework Convention on Climate Change (UNFCCC) is to achieve the stabilization of greenhouse gas (GHG) concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved within a time frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner (Article 2). This Chapter discusses Article 2 of the Convention within the framework of the main options and conditions under which it is to be implemented, reflects on past and future GHG emission trends, highlights the institutional mechanisms currently in place for the implementation of climate change and sustainable development objectives, summarizes changes from previous assessments and provides a brief roadmap for the ‘Climate Change 2007: Mitigation of Climate Change’ assessment. Defining what is dangerous anthropogenic interference with the climate system and, consequently, the limits to be set for policy purposes are complex tasks that can only be partially based on science, as such definitions inherently involve normative judegments. Decisions made in relation to Article 2 will determine the level of GHG concentrations in the atmosphere (or the corresponding climate change) that is set as the goal for policy and have fundamental implications for emission reduction pathways as well as the scale of adaptation required. The choice of a stabilization level implies the balancing of the risks of climate change (risks of gradual change and of extreme events, risk of irreversible change of the climate, including risks for food security, ecosystems and sustainable development) against the risk of response measures that may threaten economic sustainability. There is little consensus as to what constitutes anthropogenic interference with the climate system and, thereby, on how to operationalize Article 2 (high agreement, much evidence). Although any definition of ‘dangerous interference’ is by necessity based on its social and political ramifications and, as such, depends on the level of risk deemed acceptable, deep emission reductions are unavoidable in order to achieve stabilization. The lower the stabilization level, the earlier these deep reductions have to be realized (high agreement, much evidence). At the present time total annual emissions of GHGs are rising. Over the last three decades, GHG emissions have increased by an average of 1.6% per year1 with carbon dioxide (CO2) emissions from the use of fossil fuels growing at a rate of 1.9% per year. In the absence of additional policy actions,
1
these emission trends are expected to continue. It is projected that – with current policy settings – global energy demand and associated supply patterns based on fossil fuels – the main drivers of GHG emissions – will continue to grow. Atmospheric CO2 concentrations have increased by almost 100 ppm in comparison to its preindustrial level, reaching 379 ppm in 2005, with mean annual growth rates in the 2000–2005 period that were higher than those in the 1990s. The total CO2 equivalent (CO2-eq) concentration of all long-lived GHGs is currently estimated to be about 455 ppm CO2-eq, although the effect of aerosols, other air pollutants and land-use change reduces the net effect to levels ranging from 311 to 435 ppm CO2-eq (high agreement, much evidence). Despite continuous improvements in energy intensities, global energy use and supply are projected to continue to grow, especially as developing countries pursue industrialization. Should there be no substantial change in energy policies, the energy mix supplied to run the global economy in the 2025–2030 time frame will essentially remain unchanged – more than 80% of the energy supply will be based on fossil fuels, with consequent implications for GHG emissions. On this basis, the projected emissions of energy-related CO2 in 2030 are 40–110 % higher than in 2000 (with two thirds to three quarters of this increase originating in non-Annex I countries), although per capita emissions in developed countries will remain substantially higher. For 2030, GHG emission projections (Kyoto gases) consistently show a 25–90% increase compared to 2000, with more recent projections being higher than earlier ones (high agreement, much evidence). The numerous mitigation measures that have been undertaken by many Parties to the UNFCCC and the entry into force of the Kyoto Protocol in February 2005 (all of which are steps towards the implementation of Article 2) are inadequate for reversing overall GHG emission trends. The experience within the European Union (EU) has demonstrated that while climate policies can be – and are being – effective, they are often difficult to fully implement and coordinate, and require continual improvement in order to achieve objectives. In overall terms, however, the impacts of population growth, economic development, patterns of technological investment and consumption continue to eclipse the improvement in energy intensities and decarbonization. Regional differentiation is important when addressing climate change mitigation – economic development needs, resource endowments and mitigative and adaptive capacities – are too diverse across regions for a ‘one-size fits all’ approach (high agreement, much evidence). Properly designed climate change policies can be part and parcel of sustainable development, and the two can be mutually reinforcing. Sustainable development paths can
Total GHG (Kyoto gases) emissions in 2004 amounted to 49.0 GtCO2-eq, which is up from 28.7 GtCO2-eq in 1970 – a 70% increase between 1970 and 2004. In 1990 global GHG emissions were 39.4 GtCO2-eq.
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Introduction
reduce GHG emissions and reduce vulnerability to climate change. Projected climate changes can exacerbate poverty and undermine sustainable development, especially in leastdeveloped countries. Hence, global mitigation efforts can enhance sustainable development prospects in part by reducing the risk of adverse impacts of climate change. Mitigation can also provide co-benefits, such as improved health outcomes. Mainstreaming climate change mitigation is thus an integral part of sustainable development (medium agreement, much evidence). This chapter concludes with a road map of this report. Although the structure of this report (Fourth Assessment Report (AR4)) resembles the Third Assessment Report (TAR), there are distinct differences. The AR4 assigns greater weight to (1) a more detailed resolution of sectoral mitigation options and costs, (2) regional differentiation, (3) emphasizing crosscutting issues (e.g. risks and uncertainties, decision and policy making, costs and potentials, biomass, the relationships between mitigation, adaptation and sustainable development, air pollution and climate, regional aspects and issues related to the implementation of UNFCCC Article 2), and (4) the integration of all these aspects.
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Chapter 1
Chapter 1
Introduction
1.1
Introduction
The assessment ‘Climate Change 2007: Mitigation of Climate Change’ is designed to provide authoritative, timely information on all aspects of technologies and socioeconomic policies, including cost-effective measures to control greenhouse gas (GHG) emissions. A thorough understanding of future GHG emissions and their drivers, available mitigation options, mitigation potentials and associated costs and ancillary benefits is especially important to support negotiations on future reductions in global emissions. This chapter starts with a discussion of the key issues involved in Article 2 of the United Nations Framework Convention on Climate Change (UNFCCC) and of the relationship of these to emission pathways and broad mitigation options. The sections that follow reflect on past and future GHG emission trends, highlight the institutional mechanisms in place for the implementation of climate change and sustainable development objectives, summarize changes from previous assessments and provides a concise roadmap to the ‘Climate Change 2007: Mitigation of Climate Change’ assessment.
1.2
Ultimate objective of the UNFCCC
The UNFCCC was adopted in May 1992 in New York and opened for signature at the ‘Rio Earth Summit’ in Rio de Janeiro a month later. It entered into force in March 1994 and has achieved near universal ratification with ratification by 189 countries of the 194 UN member states (December 2006)2. 1.2.1
Article 2 of the Convention
Article 2 of the UNFCCC specifies the ultimate objective of the Convention and states: ‘The ultimate objective of this Convention and any related legal instruments that the Conference of the Parties may adopt is to achieve, in accordance with the relevant provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved within a time frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner’ (UN, 1992). The criterion that relates to enabling economic development to proceed in a sustainable manner is a double-edged sword. Projected anthropogenic climate change appears likely to adversely affect sustainable development, with adverse effects tending to increase with higher levels of climate change and 2
GHG concentrations (IPCC, 2007b, SPM and Chapter 19). Conversely, costly mitigation measures could have adverse effects on economic development. This dilemma facing policymakers results in (a varying degree of) tension that is manifested in the debate over the scale of the interventions and the balance to be adopted between climate policy (mitigation and adaptation) and economic development. The assessment of impacts, vulnerability and adaptation potentials is likely to be important for determinating the levels and rates of climate change which would result in ecosystems, food production or economic development being threatened to a level sufficient to be defined as dangerous. Vulnerabilities to anthropogenic climate change are strongly regionally differentiated, with often those in the weakest economic and political position being the most susceptible to damages (IPCC, 2007b, Chapter 19, Tables 19.1 and 19.3.3). Limits to climate change or other changes to the climate system that are deemed necessary to prevent dangerous anthropogenic interference with the climate system can be defined in terms of various – and often quite different – criteria, such as concentration stabilization at a certain level, global mean temperature or sea level rise or levels of ocean acidification. Whichever limit is chosen, its implementation would require the development of consistent emission pathways and levels of mitigation (Chapter 3). 1.2.2
What is dangerous interference with the climate system?
Defining what is dangerous interference with the climate system is a complex task that can only be partially supported by science, as it inherently involves normative judgements. There are different approaches to defining danger, and an interpretation of Article 2 is likely to rely on scientific, ethical, cultural, political and/or legal judgements. As such, the agreement(s) reached among the Parties in terms of what may constitute unacceptable impacts on the climate system, food production, ecosystems or sustainable economic development will represent a synthesis of these different perspectives. Over the past two decades several expert groups have sought to define levels of climate change that could be tolerable or intolerable, or which could be characterized by different levels of risk. In the late 1980s, the World Meteorological Organization (WMO)/International Council of Scientific Unions (ICSU)/ UN Environment Programme (UNEP) Advisory Group on Greenhouse Gases (AGGG) identified two main temperature indicators or thresholds with different levels of risk (Rijsberman and Swart, 1990). Based on the available knowledge at the time a 2ºC increase was determined to be ‘an upper limit beyond which the risks of grave damage to ecosystems, and of nonlinear responses, are expected to increase rapidly’. This early
http://unfccc.int/essential_background/convention/items/2627.php. 190 ratifications - one from the European Union.
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work also identified the rate of change to be of importance to determining the level of risk, a conclusion that has subsequently been confirmed qualitatively (IPCC, 2007b, Chapters 4 and 19). More recently, others in the scientific community have reached conclusions that point in a similar direction ‘that global warming of more than 1°C, relative to 2000, will constitute “dangerous” climate change as judged from likely effects on sea level and extermination of species’ (Hansen et al., 2006). Probabilistic assessments have also been made that demonstrate how scientific uncertainties, different normative judgments on acceptable risks to different systems (Mastrandrea and Schneider, 2004) and/or interference with the climate system (Harvey, 2007) affect the levels of change or interference set as goals for policy (IPCC, 2007b, Chapter 19). From an economic perspective, the Stern Review (Stern, 2006) found that in order to minimise the most harmful consequences of climate change, concentrations would need to be stabilized below 550 ppm CO2-eq. The Review further argues that any delay in reducing emissions would be ‘would be costly and dangerous’. This latter conclusion is at variance with the conclusions drawn from earlier economic analyses which support a slow ‘ramp up’ of climate policy action (Nordhaus, 2006) and, it has been argued, is a consequence of the approach taken by the Stern Review to intergenerational equity (Dasgupta, 2006). The IPCC Third Assessment Report (TAR) identified five broad categories of reasons for concern that are relevant to Article 2: (1) Risks to unique and threatened systems, (2) risks from extreme climatic events, (3) regional distribution of impacts, (4) aggregate impacts and (5) risks from large-scale discontinuities. The Fourth Assessment Report (AR4) focuses on Key Vulnerabilities relevant to Article 2, which are broadly categorized into biological systems, social systems, geophysical systems, extreme events and regional systems (IPCC, 2007b, Chapter 19). The implications of different interpretations of dangerous anthropogenic interference for future emission pathways are reviewed in IPCC (2007b), Chapter 9 and also in Chapter 3 of this report. The literature confirms that climate policy can substantially reduce the risk of crossing thresholds deemed dangerous (IPCC, 2007b, SPM and Chapter 19; Chapter 3, Section 3.5.2 of this report). While the works cited above are principally scientific (expertled) assessments, there is also an example of governments seeking to define acceptable levels of climate change based on interpretations of scientific findings. In 2005, the EU Council (25 Heads of Government of the European Union) agreed that – with a view to achieving the ultimate objective of the Convention – the global annual mean surface temperature increase should not exceed 2ºC above pre-industrial levels (CEU, 2005).
3
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1.2.3
Issues related to the implementation of Article 2
Decisions made in relation to Article 2 will determine the level of climate change that is set as the goal for policy and have fundamental implications for emission reduction pathways, the feasibility, timing and scale of adaptation required and the magnitude of unavoidable losses. The emission pathways which correspond to different GHG or radiative forcing stabilization levels and consequential global warming are reviewed in Chapter 3 (see Tables 3.9 and 3.10). The potential consequences of two hypothetical limits can provide an indication of the differing scales of mitigation action that depend on Article 2 decisions: A 2ºC above pre-industrial limit on global warming would implies that emissions peak within the next decade and be reduced to less than 50% of the current level by 20503; a 4ºC limit would imply that emissions may not have to peak until well after the middle of the century and could still be well above 2000 levels in 2100. In relation to the first hypothetical limt, the latter would have higher levels of adaptation costs and unavoidable losses, but carry lower mitigation costs. Issues related to the mitigation, adaptation and sustainable development aspects of the implementation of Article 2 thus include, among others, the linkages between sustainable development and the adverse effects climate change, the need for equity and cooperation and the recognition of common but differentiated responsibilities and respective capabilities as well as the precautionary principle (see Section 1.4.1 for more detail on relevant UNFCCC Articles that frame these issues). In this context, risk management issues which take into account several key aspects of the climate change problem, such as inertia, irreversibility, the risk of abrupt or catastrophic changes and uncertainty, are introduced in this section and discussed in more detail in Chapters 2, 3 and 11. 1.2.3.1
Sustainable development
Sustainable development has environmental, economic and social dimensions (see Chapter 2, Section 2.1). Properly designed climate change responses can be part and parcel of sustainable development, and the two can be mutually reinforcing (Section 2.1). Mitigation, by limiting climate change, can conserve or enhance natural capital (ecosystems, the environment as sources and sinks for economic activities) and prevent or avoid damage to human systems and, thereby, contribute to the overall productivity of capital needed for socio-economic development, including mitigative and adaptive capacity. In turn, sustainable development paths can reduce vulnerability to climate change and reduce GHG emissions. The projected climate changes can exacerbate poverty and thereby undermine sustainable development (see, for example, IPCC, 2007b, Chapters 6, Section 9.7 and 20.8.3), especially in
For the best-guess climate sensitivity and the lowest range of multigas stabilization scenarios found in the literature which show a warming of about 2-2.4ºC above preindustrial temperatures (Chapter 3, section 3.5.2 and Table 3.10).
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developing countries, which are the most dependent on natural capital and lack financial resources (see Chapter 2 and Stern (2006)). Hence global mitigation efforts can enhance sustainable development prospects in part by reducing the risk of adverse impacts of climate change (see also Chapter 12). 1.2.3.2
Adaptation and mitigation
Adaptation and mitigation can be complementary, substitutable or independent of each other (see IPCC, 2007b, Chapter 18). If complementary, adaptation reduces the costs of climate change impacts and thus reduces the benefits of mitigation. Although adaptation and mitigation may be substitutable up to a certain point, they are never perfect substitutes for each other since mitigation will always be required to avoid ‘dangerous’ and irreversible changes to the climate system. Irrespective of the scale of the mitigation measures that are implemented in the next 10–20 years, adaptation measures will still be required due to the inertia in the climate system. As reported in IPCC, 2007b, Chapter 19 (and also noted in Stern (2006)), changes in the climate are already causing setbacks to economic and social development in some developing countries with temperature increases of less than 1°C. Unabated climate change would increase the risks and costs very substantially (IPCC, 2007b, Chapter 19). Both adaptation and mitigation depend on capital assets, including social capital, and both affect capital vulnerability and GHG emissions (see Chapter 2, Section 2.5.2). Through this mutual dependence, both are tied to sustainable development (see Sections 2.5, 11.8 and 11.9, 12.2 and 12.3). The stabilization of GHG concentrations and, in particular, of the main greenhouse gas, CO2, requires substantial emission reductions, well beyond those built into existing agreements such as the Kyoto Protocol. The timing and rate of these reductions depend on the level of the climate goal chosen (see Chapter 3.3.5.1). 1.2.3.3
Inertia
Inertia in both the climate and socio-economic systems would need to be taken into account when mitigation actions are being considered. Mitigation actions aimed at specific climate goals would need to factor in the response times of the climate system, including those of the carbon cycle, atmosphere and oceans. A large part of the atmospheric response to radiative forcing occurs on decadal time scales, but a substantial component is linked to the century time scales of the oceanic response to the same forcing changes (Meehl et al., 2007). Once GHG concentrations are stabilized global mean temperature would very likely stabilize within a few decades, although a further slight increase may still occur over several centuries (Meehl et al., 2007). The rise in sea level, however, would continue for many centuries after GHG stabilization due to both ongoing heat uptake by the oceans and the long time scale of ice sheet response to warming (Meehl et al., 2007). The time scales
for mitigation are linked to technological, social, economic, demographic and political factors. Inertia is a characteristic of the energy system with its long-life infrastructures, and this inertia is highly relevant to how fast GHG concentrations can be stabilized (Chapter 11.6.5). Adaptation measures similarly exhibit a range of time scales, and there can be substantial lead times required before measures can be implemented and subsequently take effect, particularly when it involves infrastructure (IPCC, 2007b, Chapter 17). The consequence of inertia in both the climate and socioeconomic systems is that benefits from mitigation actions initiated now – in the short term – would lead to significant changes in the climate being avoided several decades further on. This means that mitigation actions need to be implemented in the short term in order to have medium- and long-term benefits and to avoid the lock in of carbon intensive technologies (Chapter 11.6.5). 1.2.3.4
Uncertainty and risk
Uncertainty in knowledge is an important aspect in the implementation of Article 2, whether it is assessing future GHG emissions or the severity of climate change impacts and regional changes, evaluating these impacts over many generations, estimating mitigation costs or evaluating the level of mitigation action needed to reduce risk. Notwithstanding these uncertainties, mitigation will reduce the risk of both global mean and regional changes and the risk of abrupt changes in the climate system (see Chapter 2, Section 2.3). There may be risks associated with rapid and/or abrupt changes in the climate and the climate system as a result of human interference (Solomon et al., 2007; IPCC, 2007b, Chapter 19 Tables 19.1 and 19.3.5-7). These include changes in climate variability (El Nino Southern Oscillation, monsoons); a high likelihood that warming will lead to an increase in the risk of many extreme events, including floods, droughts, heat waves and fires, with increasing levels of adverse impacts; a risk that a 1–2ºC sustained global warming (versus the temperature at present) would lead to a commitment to a large sea-level rise due to at least the partial deglaciation of both ice sheets; an uncertain risk of a shutdown of the North Atlantic Meridional Overturning Circulation; a large increase in the intensity of tropical cyclones with increasing levels of adverse impacts as temperatures increase; the risk that positive feedbacks from warming may cause the release of CO2 or methane (CH4) from the terrestrial biosphere and soils (IPCC, 2007b, Chapter 19 Tables 19.1 and 19.3.5-7). In the latter case, a positive climate– carbon cycle feedback would reduce the land and ocean uptake of CO2, implying a reduction of the allowable emissions required to achieve a given atmospheric CO2 stabilization level (Meehl et al., 2007, Executive Summary).
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1.2.3.5
Chapter 1
Irreversibility
Irreversibility is an important aspect of the climate change issue, with implications for mitigation and adaptation responses. The response of the climate system to anthropogenic forcing is likely to be irreversible over human time scales, and much of the damage is likely to be irreversible even over longer time scales. Mitigation and adaptation will often require investments involving sunk (irreversible) costs in new technologies and practices (Sections 2.2.3, 11.6.5; IPCC, 2007b, Chapter 17). Decision-makers will need to take into account these environmental, socio-economic and technological irreversibilities in deciding on the timing and scale of mitigation action. 1.2.3.6
Public good
The climate system tends to be overused (excessive GHG concentrations) because of its natural availability as a resource whose access is open to all free of charge. In contrast, climate protection tends to be underprovided. In general, the benefits of avoided climate change are spatially indivisible, freely available to all (non-excludability), irrespective of whether one is contributing to the regime costs or not. As regime benefits by one individual (nation) do not diminish their availability to others (non-rivalry), it is difficult to enforce binding commitments on the use of the climate system4 (Kaul et al., 1999; 2003). This may result in ‘free riding’, a situation in which mitigation costs are borne by some individuals (nations) while others (the ‘free riders’) succeed in evading them but still enjoy the benefits of the mitigation commitments of the former. The incentive to evade mitigation costs increases with the degree of substitutability among individual mitigation efforts (mitigation is largely additive) and with the inequality of the distribution of net benefits among regime participants. However, individual mitigation costs decrease with efficient mitigation actions undertaken by others. Because mitigation efforts are additive, the larger the number of participants, the smaller the individual cost of providing the public good – in this case, climate system stabilization. Cooperation requires the sharing of both information on climate change and technologies through technology transfers as well as the coordination of national actions lest the efforts required by the climate regime be underprovided. 1.3.3.7
Equity
Equity is an ethical construct that demands the articulation and implementation of choices with respect to the distribution of rights to benefits and the responsibilities for bearing the costs resulting from particular circumstances – for example,
4 5
climate change – within and among communities, including future generations. Climate change is subject to a very asymmetric distribution of present emissions and future impacts and vulnerabilities. Equity can be elaborated in terms of distributing the costs of mitigation or adaptation, distributing future emission rights and ensuring institutional and procedural fairness (Chapter 13, Section 13.3.4.3). Equity also exhibits preventative (avoidance of damage inflicted on others), retributive (sanctions), and corrective elements (e.g. ‘common but differentiated responsibilities’) (Chapter 2, Section 2.6), each of which has an important place in the international response to the climate change problem (Chapter 13).
1.3 Energy, emissions and trends in Research and Development – are we on track? 1.3.1
Review of the last three decades
Since pre-industrial times, increasing emissions of GHGs due to human activities have led to a marked increase in atmospheric concentrations of the long-lived GHG gases carbon dioxide (CO2), CH4, and nitrous oxide (N2O), perfluorocarbons PFCs, hydrofluorocarbons (HFCs) and sulphur hexafluoride (SF6) and ozone-depleting substances (ODS; chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), halons) and the humaninduced radiative forcing of the Earth’s climate is largely due to the increases in these concentrations. The predominant sources of the increase in GHGs are from the combustion of fossil fuels. Atmospheric CO2 concentrations have increased by almost 100 ppm in comparison to its preindustrial levels, reaching 379 ppm in 2005, with mean annual growth rates in the 2000–2005 period that were higher than those in the 1990s. The direct effect of all the long-lived GHGs is substantial, with the total CO2 equivalent concentration of these gases currently being estimated to be around 455 ppm CO2-eq5 (range: 433–477 ppm CO2-eq). The effects of aerosol and landuse changes reduce radiative forcing so that the net forcing of human activities is in the range of 311 to 435 ppm CO2-eq, with a central estimate of about 375 ppm CO2-eq. A variety of sources exist for determining global and regional GHG and other climate forcing agent trends. Each source has its strengths and weaknesses and uncertainties. The EDGAR database (Olivier et al., 2005, 2006) contains global GHG emission trends categorized by broad sectors for the period 1970–2004, and Marland et al. (2006) report CO2 emissions on a global basis. Both databases show a similar temporal evolution of emissions. Since 1970, the global warming potential (GWP)-
Resulting in a prisoners’ dilemma situation because of insufficient incentives to cooperate. Radiative forcing (Forster et al., 2007) is converted to CO2 equivalents using the inversion of the expression Q (W/m2) = 5.35 × ln (CO2/278) (see Solomon et al., 2007, Table TS-2 footnote b).
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Introduction
Figure 1.1a Global anthropogenic greenhouse gas trends, 1970–2004.
Gt CO2eq/yr HFCs, PFCs, SF6
0 5
N2O other1) N2O agriculture
0 10
CH4 other2) CH4 waste
5
CH4 agriculture CH4 energy3)
0 10 5
CO2 decay and peat4)
0
CO2 deforestation5) 6)
30
One-hundred year global warming potentials (GWPs) from the Intergovernmental Panel on Climate Change (IPCC) 1996 (SAR) were used to convert emissions to CO2 equivalents (see the UNFCCC reporting guidelines). Gases are those reported under UNFCCC reporting guidelines. The uncertainty in the graph is quite large for CH4 and N2O (of the order of 30–50%) and even larger for CO2 from agriculture and forestry. Notes: 1. Other N2O includes industrial processes, deforestation/savannah burning, waste water and waste incineration. 2. Other is CH4 from industrial processes and savannah burning. 3. Including emissions from bio energy production and use. 4. CO2 emissions from decay (decomposition) of above ground biomass that remains after logging and deforestation and CO2 from peat fires and decay of drained peat soils. 5. As well as traditional biomass use at 10% of total, assuming 90% is from sustainable biomass production. Corrected for the 10% of carbon in biomass that is assumed to remain as charcoal after combustion. 6. For large-scale forest and scrubland biomass burning averaged data for 1997-2002 based on Global Fire Emissions Data base satellite data. 7. Cement production and natural gas flaring. 8. Fossil fuel use includes emissions from feedstocks. Source: Adapted from Olivier et al., 2005; 2006; Hooijer et al., 2006
CO2 other7)
25 20 15
N 2O 7.9%
CO2 fossil fuel use8)
F-gases 1.1%
10 CH4 14.3%
5 0 1970
1980
1990 2000 2004 CO2 fossil fuel use 56.6%
50 40 30
Total GHG
20
CO2 (deforestation, decay of biomass, etc) 17.3% CO2 (other) 2.8%
10
Figure 1.1b Global anthropogenic greenhouse gas emissions in 2004.
0 1970
1980
1990
2000 2004
weighted emissions of GHGs (not including ODS which are controlled under the Montreal Protocol), have increased by approximately 70%, (24% since 1990), with CO2 being the largest source, having grown by approximately 80% (28% since 1990) to represent 77% of total anthropogenic emissions in 2004 (74% in 1990) (Figure 1.1). Radiative forcing as a result of increases in atmospheric CO2 concentrations caused
Source: Adapted from Olivier et al., 2005, 2006
by human activities since the preindustrial era predominates over all other radiative forcing agents (IPCC, 2007a, SPM). Total CH4 emissions have risen by about 40% from 1970 (11% from 1990), and on a sectoral basis there has been an 84% (12% from 1990) increase from combustion and the use of fossil fuels, while agricultural emissions have remained roughly stable due to compensating falls and increases in rice and livestock 103
Introduction
Chapter 1
Gt CO2 yr
10
Electricity plants
9 8 7 6
2
Industry (excl. cement) Road transport Residential and service sectors Deforestation 1) Other 2) Refineries etc.
1
International transport 3)
5 4 3
0 1970
1980
1990
2000
Figure 1.2: Sources of global CO2 emissions, 1970–2004 (only direct emissions by sector). 1) Including
fuelwood at 10% net contribution. For large-scale biomass burning, averaged data for 1997–2002 are based on the Global Fire Emissions Database satellite data (van der Werf et al., 2003). Including decomposition and peat fires (Hooijer et al., 2006). Excluding fossil fuel fires. 2) Other domestic surface transport, non-energetic use of fuels, cement production and venting/flaring of gas from oil production. 3) Including aviation and marine transport. Source: Adapted from Olivier et al., 2005; 2006).
production, respectively. N2O emissions have grown by 50% since 1970 (11% since 1990), mainly due to the increased use of fertilizer and the aggregate growth of agriculture. Industrial process emissions of N2O have fallen during this period. The use and emissions of all fluorinated gases (including those controlled under the Montreal Protocol) decreased substantially during 1990–2004. The emissions, concentrations and radiative forcing of one type of fluorinated gas, the HFCs, grew rapidly during this period as these replaced ODS; in 2004, CFCs were estimated to constitute about 1.1% of the total GHG emissions (100-year GWP) basis. Current annual emissions of all fluorinated gases are estimated at 2.5 GtCO2-eq, with HFCs at 0.4 GtCO2-eq. The stocks of these gases are much larger and currently represent about 21 GtCO2-eq. The largest growth in CO2 emissions has come from the power generation and road transport sectors, with the industry, households and the service sector6 remaining at approximately the same levels between 1970 and 2004 (Figure 1.2). By 2004, CO2 emissions from power generation represented over 27% of the total anthropogenic CO2 emissions and the power sector was by far its most important source. Following the sectoral breakdown adopted in this report (Chapters 4–10), in 2004 about 26% of GHG emissions were derived from energy supply (electricity and heat generation), about 19% from industry, 14%
6 7 8
from agriculture7, 17% from land use and land-use change8, 13% from transport, 8% from the residential, commercial and service sectors and 3% from waste (see Figure 1.3). These values should be regarded as indicative only as some uncertainty remains, particularly with regards to CH4 and N2O emissions, for which the error margin is estimated to be in the order of 30–50%, and CO2 emissions from agriculture, which have an even larger error margin. Since 1970, GHG emissions from the energy supply sector have grown by over 145%, while those from the transport sector have grown by over 120%; as such, these two sectors show the largest growth in GHG emissions. The industry sector’s emissions have grown by close to 65%, LULUCF (land use, land-use change and forestry) by 40% while the agriculture sector (27%) and residential/commercial sector (26%) have experienced the slowest growth between 1970 and 2004. The land-use change and forestry sector plays a significant role in the overall carbon balance of the atmosphere. However, data in this area are more uncertain than those for other sectors. The Edgar database indicates that, in 2004, the share of CO2 emissions from deforestation and the loss of carbon from soil decay after logging constituted approximately 7–16% of the total GHG emissions (not including ODS) and between 11 and 28% of fossil CO2 emissions. Estimates vary considerably.
Direct emissions by sector; i.e., data do not include indirect emissions. N2O and CH4 emissions (CO2 emissions are small; compare with Chapter 8) and not counting land clearance. The proportion of emissions of N2O and CH4 are higher – around 85 and 45% (±5%), respectively. Emissions from agricultural soils not related to land clearance are quite small – of an order of 40 MtCO2 per year in 2005 (Chapter 8). Deforestation, including biofuel combustion, assuming 90% sustainable production, biomass burning, CO2 emissions from the decay of aboveground biomass after logging and deforestation and from peat fires and decay of peat soils.
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Introduction
Gt CO2-eq. F-gases N2 O
12
CH4 CO2
10
8
6
4
2
0
1990 2004 Energy supply 1)
1990 2004 Transport 2)
1990 2004 Residential and commercial buildings 3)
1990 2004 Industry 4)
1990 2004 Agriculture 5)
1990 2004 LULUCF/ Forestry 6)
1990 2004 Waste and wastewater 7)
Figure 1.3a: GHG emissions by sector in 1990 and 2004. Source: Adapted from Olivier et al., 2005, 2006.
Waste and wastewater7) 2.8% Energy supply1) 25.9%
Forestry6) 17.4%
Agriculture5) 13.5%
One-hundred year GWPs from IPCC, 1996 (Second Assessment Report) were used to convert emissions to CO2 equivalents. The uncertainty in the graph is quite large for CH4 and N2O (of the order of 30–50%) and even larger for CO2 from agriculture and forestry. For large-scale biomass burning, averaged activity data for 1997–2002 were used from the Global Fire Emissions Database based on satellite data. Peat (fire and decay) emissions are based on recent data from WL/Delft Hydraulics. 1)
Transport2) 13.1%
Industry4) 19.4%
Figure 1.3b: GHG emissions by sector in 2004.
Residential and commercial buildings3) 7.9%
2)
3)
4)
5)
Source: Adapted from Olivier et al., 2005; 2006. 6)
7)
Excluding refineries, coke ovens which are included in industry. Including international transport (bunkers), excluding fisheries; excluding off-road agricultural and forestry vehicles and machinery. Including traditional biomass use. Emissions reported in Chapter 6 include the sector’s share in emissions caused by centralized electricity generation so that any mitigation achievements in the sector resulting from lower electricity use are credited to the sector. Including refineries and coke ovens. Emissions reported in Chapter 7 include the sector’s share in emissions caused by centralized electricity generation so that any mitigation achievements in the sector resulting from lower electricity use are credited to the sector. Including agricultural waste burning and savannah burning (nonCO2). CO2 emissions and/or removals from agricultural soils are not estimated in this database. Data include CO2 emissions from deforestation, CO2 emissions from decay (decomposition) of aboveground biomass that remains after logging and deforestation and CO2 from peat fires and decay of drained peat soils. Chapter 9 reports emissions from deforestation only. Includes landfill CH4, wastewater CH4 and N2O, and CO2 from waste incineration (fossil carbon only). 105
Introduction
3.0 Non-Annex I: Population 80.3%
2.5
25
Annex I non-Annex I
2.0
20
0 0
1,000
Middle East: 3.8%
5
Other non-Annex I: 2.0% Europe Annex II: and M & T 11,4%
10
JANZ: 5.2%
USA & Canada: 19,4%
15
EIT Annex I: 9.7%
Average Annex I: 16,1 t CO2eq/cap
Latin America & Carribean: 10.3%
Non-Annex I East Asia: 17,3%
Average non-Annex I: 4,2 t CO2eq/cap South Asia:13,1%
2,000 3,000 4,000 5,000 Cumulative population in million
6,000
0.5
Non-Annex I East Asia: 17,3%
0 7,000
GHG/GDP kg CO2eq/US$ 0.683 1.055
1.5 1.0
Africa: 7.8%
Share in global GDP 56.6% 43.4%
Other non-Annex I: 2.0%
Middle East: 3.8% Latin America & Carribean: 10.3%
Annex I: Population 19.7%
kg CO2eq/US$ GDPppp (2000)
Africa: 7.8%
30
t CO2eq/cap
EIT Annex I: 9.7%
35
Chapter 1
0
10,000
South Asia: 13,1%
USA & Canada: 19,4%
JANZ: 5.2%
Europe Annex II and M & T: 11,4%
20,000 30,000 40,000 50,000 Cumulative GDPppp (2000) in billion US$
60,000
Figure 1.4a: Distribution of regional per capita GHG emissions (all Kyoto gases including those from land-use) over the population of different country groupings in 2004. The percentages in the bars indicate a region’s share in global GHG emissions.
Figure 1.4b: Distribution of regional GHG emissions (all Kyoto gases including those from land-use) per USD of GDPppp over the GDP of different country groupings in 2004. The percentages in the bars indicate a region’s share in global GHG emissions.
Source: Adapted from Bolin and Khesgi, 2001) using IEA and EDGAR 3.2 database information (Olivier et al., 2005, 2006).
Source: IEA and EDGAR 3.2 database information (Olivier et al., 2005, 2006).
Note: Countries are grouped according to the classification of the UNFCCC and its Kyoto Protocol; this means that countries that have joined the European Union since then are still listed under EIT Annex I. A full set of data for all countries for 2004 was not available. The countries in each of the regional groupings include: • EIT Annex I: Belarus, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Russian Federation, Slovakia, Slovenia, Ukraine • Europe Annex II & M&T: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom; Monaco and Turkey • JANZ: Japan, Australia, New Zealand. • Middle East: Bahrain, Islamic Republic of Iran, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, United Arab Emirates, Yemen • Latin America & the Caribbean: Antigua & Barbuda, Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Lucia, St. Kitts-NevisAnguilla, St. Vincent-Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela • Non-Annex I East Asia: Cambodia, China, Korea (DPR), Laos (PDR), Mongolia, Republic of Korea, Viet Nam. • South Asia: Afghanistan, Bangladesh, Bhutan, Comoros, Cook Islands, Fiji, India, Indonesia, Kiribati, Malaysia, Maldives, Marshall Islands, Micronesia, (Federated States of), Myanmar, Nauru, Niue, Nepal, Pakistan, Palau, Papua New Guinea, Philippine, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu • North America: Canada, United States of America. • Other non-Annex I: Albania, Armenia, Azerbaijan, Bosnia Herzegovina, Cyprus, Georgia, Kazakhstan, Kyrgyzstan, Malta, Moldova, San Marino, Serbia, Tajikistan, Turkmenistan, Uzbekistan, Republic of Macedonia • Africa: Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Congo, Democratic Republic of Congo, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Togo, Tunisia, Uganda, United Republic of Tanzania, Zambia, Zimbabwe
There are large emissions from deforestation and other landuse change activities in the tropics; these have been estimated in IPCC (2007a) for the 1990s to have been 5.9 GtCO2-eq, with a large uncertainty range of 1.8–9.9 GtCO2-eq (Denman et al., 2007). This is about 25% (range: 8–42%) of all fossil fuel and cement emissions during the 1990s. The underlying factors accounting for the large range in the estimates of tropical deforestation and land-use changes emissions are complex and not fully resolved at this time (Ramankutty et al., 2006). For the Annex I Parties that have reported LULUCF sector data to the UNFCCC (including agricultural soils and forests) since 1990, the aggregate net sink reported for emissions and removals over the period up to 2004 average out to approximately 1.3 GtCO2eq (range: –1.5 to –0.9 GtCO2-eq)9. On a geographic basis, there are important differences between regions. North America, Asia and the Middle East have
9
driven the rise in emissions since 1972. The former countries of the Soviet Union have shown significant reductions in CO2 emissions since 1990, reaching a level slightly lower than that in 1972. Developed countries (UNFCCC Annex I countries) hold a 20% share in the world population but account for 46.4% of global GHG emissions. In contrast, the 80% of the world population living in developing countries (non-Annex I countries) account for 53.6% of GHG emissions (see Figure 1.4a). Based on the metric of GHG emission per unit of economic output (GHG/GDPppp)10, Annex I countries generally display lower GHG intensities per unit of economic production process than non-Annex I countries (see Figure 1.4b). The promotion of energy efficiency improvements and fuel switching are among the most frequently applied policy measures that result in mitigation of GHG emissions. Although they may not necessarily be targeted at GHG emission
Data for the Russian Federation is not included in the UNFCCC data set. Chapter 7 estimates the Russian sink for 1990–2000 to be 370–740 MtCO2/year, which would add up to approximately 28–57% of the average sink reported here. 10 The GDPppp metric is used for illustrative purposes only for this report.
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mitigation, such policy measures do have a strong impact in lowering the emission level from where it would be otherwise. According to an analysis of GHG mitigation activities in selected developing countries by Chandler et al. (2002), the substitution of gasoline-fuelled cars with ethanol-fuelled cars and that of conventional CHP (combined heat and power; also cogeneration) plants with sugar-cane bagasse CHP plants in Brazil resulted in an estimated carbon emission abatement of 23.5 MtCO2 in 2000 (actual emissions in 2000: 334 MtCO2). According to the same study, economic and energy reforms in China curbed the use of low-grade coal, resulting in avoided emissions of some 366 MtCO2 (actual emissions: 3,100 MtCO2). In India, energy policy initiatives including demandside efficiency improvements are estimated to have reduced emissions by 66 MtCO2 (compared with the actual emission level of 1,060 MtCO2). In Mexico, the switch to natural gas, the promotion of efficiency improvements and lower deforestation are estimated to have resulted in 37 MtCO2 of emission reductions, compared with actual emissions of 685 MtCO2. For the EU-25 countries, the European Environment Agency (EEA, 2006) provides a rough estimate of the avoided CO2 emissions from public electricity and heat generation due to efficiency improvements and fuel switching. If the efficiency and fuel mix had remained at their 1990 values, emissions in 2003 would have been some 34% above actual emissions, however linking these reductions to specific policies was found to be difficult. For the UK and Germany about 60% of the reductions from 1990 to 2000 were found to be due to factors other than the effects of climate-related policies (Eichhammer et al., 2001, 2002). Since 2000, however, many more policies have been put into place, including those falling under the European Climate Change Programme (ECCP), and significant progress has been made, including the establishment of the EU Emissions Trading Scheme (EU ETS) (CEC, 2006). A review of the effectiveness of the first stage of the ECCP reported that about one third of the potential reductions had been fully implemented by mid 200611. Overall EU-25 emissions in 2004 were 0.9% lower than in the base year, and the European Commission (EC) assessed the EC Kyoto target (8% reduction relative to the base year) to be within reach under the conditions that (1) all additional measures currently under discussion are put into force in time, (2) Kyoto mechanisms are used to the full extent planned and (3) removals from Articles 3.3 and 3.4 activities (carbon sinks) contribute to the extent projected (CEC, 2006). Overall this shows that climate policies can be effective, but that they are difficult to fully implement and require continual improvement in order to achieve the desired objectives.
Introduction
1.3.1.1
Energy supply
Global primary energy use almost doubled from 5,363 Mtoe (225 EJ) in 1970 to 11,223 Mtoe (470 EJ) in 2004, with an average annual growth of 2.2% over this period. Fossil fuels accounted for 81% of total energy use in 2004 – slightly down from the 86% more than 30 years ago, mainly due to the increase in the use of nuclear energy. Despite the substantial growth of non-traditional renewable forms of energy, especially wind power, over the last decade, the share of renewables (including traditional biomass) in the primary energy mix has not changed compared with 1970 (see Chapter 4, Section 4.2). 1.3.1.2
Intensities
The Kaya identity (Kaya, 1990) is a decomposition that expresses the level of energy related CO2 emissions as the product of four indicators: (1) carbon intensity (CO2 emissions per unit of total primary energy supply (TPES)), (2) energy intensity (TPES per unit of GDP), (3) gross domestic product per capita (GDP/cap) and (4) population. The global average growth rate of CO2 emissions between 1970 and 2004 of 1.9% per year is the result of the following annual growth rates: population 1.6%, GDP/cap12 1.8%, energy-intensity of –1.2% and carbon-intensity –0.2% (Figure 1.5). A decomposition analysis according to the refined Laspeyeres index method (Sun, 1998; Sun and Ang, 2000) is shown in Figure 1.6. Each of the three stacked bars refers to 10-year periods and indicates how the net change in CO2 emissions of that decade can be attributed to the four indicators of the Kaya identity. These contributions – to tonnes of CO2 emissions – can be positive or negative, and their sum equals the net emission change (shown for each decade by the black line). GDP/capita and population growth were the main drivers of the increase in global emissions during the last three decades of the 20th century. However, consistently declining energy intensities indicate structural changes in the global energy system. The role of carbon intensity in offsetting emission growth has been declining over the last two decades. The reduction in carbon intensity of energy supply was the strongest between 1980 and 1990 due to the delayed effect of the oil price shocks of the 1970s, and it approached zero towards the year 2000 and reversed after 2000 At the global scale, declining carbon and energy intensities have been unable to offset income effects and population growth and, consequently, carbon emissions have risen. Under the reference scenario of the International Energy Agency (IEA, 2006a) these trends are expected to remain valid until 2030; in particular, energy is not expected to be further decarbonized under this baseline scenario.
11 See Table 1 of CEC (2006). Second stage ECCP (ECCP2) policies are being finalized. 12 Purchasing power parity (PPP) at 2000 prices and exchange rates.
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Index 1970 = 1 3,0
Income (GDP-ppp)
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1,0 0,8 0,6 0,4 1970
1975
1980
1985
1990
1995
2000
Emission intensity (CO2/GDP-ppp)
Figure 1.5: Intensities of energy use and CO2 emissions, 1970–2004. Data Source: IEA data
Of the major countries and groups of countries – North America, Western Europe, Japan, China, India, Brazil, Transition Economies – only the Transition Economies (refers to 1993–2003 only) and, to a lesser extent, the group of the EU15 have reduced their CO2 emissions in absolute terms.
14
The decline of the carbon content of energy (CO2/TPES) was the highest in Western Europe, but the effect led only to a slight reduction of CO2 in absolute terms. Together with Western Europe and the Transition Countries, USA/Canada, Japan and – to a much lesser extent – Brazil have also reduced their carbon intensity.
Gt CO2 observations
scenarios
12 10 8 Population 6 4
Income per capita (GDP-ppp/Pop)
2
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0 -2
Energy intensity (TPES/GDP-ppp)
-4 -6 -8 1970-80
1980-90
1990-2000
2000-10
2010-20
2020-30
Figure 1.6: Decomposition of global energy-related CO2 emission changes at the global scale for three historical and three future decades. Sources: IEA data World Energy Outlook 2006 (IEA, 2006a)
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Introduction
Declining energy intensities observed in China and India have been partially offset by increasing carbon intensities (CO2/ TPES) in these countries. It appears that rising carbon intensities accompany the early stages of the industrialization process, which is closely linked to accelerated electricity generation mainly based on fossil fuels (primarily coal). In addition, the emerging but rapidly growing transport sector is fuelled by oil, which further contributes to increasing carbon intensities. Stepped-up fossil fuel use, GDP/capita growth and, to a lesser extent, population growth have resulted in the dramatic increase in carbon emissions in India and China. The Transition Economies of Eastern Europe and the former Soviet Union suffered declining per capita incomes during the 1990s as a result of their contracting economies and, concurrently, total GHG emissions were greatly reduced. However, the continued low level of energy efficiency in using coal, oil and gas has allowed only moderate improvements in carbon and energy intensities. Despite the economic decline during the 1990s, this group of countries accounted for 12% of global CO2 emissions in 2003 (Marland et al., 2006). The challenge – an absolute reduction of global GHG emissions – is daunting. It presupposes a reduction of energy and carbon intensities at a faster rate than income and population growth taken together. Admittedly, there are many possible combinations of the four Kaya identity components, but with the scope and legitimacy of population control subject to ongoing debate, the remaining two technology-oriented factors, energy and carbon intensities, have to bear the main burden. 1.3.1.3
Energy security
With international oil prices fluctuating around 70 USD per barrel (Brent Crude in the first half of 2006; EIA, 2006a) and with prices of internationally traded natural gas, coal and uranium following suit, concerns of energy supply security are back on the agenda of many public and private sector institutions. Consequently, there is renewed public interest in alternatives to fossil fuels, especially to oil, resulting in new technology initiatives to promote hydrogen, biofuels, nuclear power and renewables (Section 1.3.1.3). Higher oil prices also tend to open up larger markets for more carbon-intensive liquid fuel production systems, such as shale oil or tar sands. However, first and foremost, energy security concerns tend to invigorate a higher reliance on indigenous energy supplies and resources. Regions where coal is the dominant domestic energy resource tend to use more coal, especially for electricity generation, which increases GHG emissions. In recent years, intensified coal use has been observed for a variety of reasons in developing Asian countries, the USA and some European countries. In a number of countries, the changing relative prices of coal to natural gas have changed the dispatch order in power generation in favour of coal.
Energy security also means access to affordable energy services by those people – largely in developing countries – who currently lack such access. It is part and parcel of sustainable development and plays a non-negligible role in mitigating climate change. Striving for enhanced energy security can impact GHG emissions in opposite ways. On the one hand, GHG emissions may be reduced as the result of a further stimulation of rational energy use, efficiency improvements, innovation and the development of alternative energy technologies with inherent climate benefits. On the other hand, measures supporting energy security may lead to higher GHG emissions due to stepped-up use of indigenous coal or the development of lower quality and unconventional oil resources. 1.3.2
Future outlook
1.3.2.1
Energy supply
A variety of projections of the energy picture have been made for the coming decades. These differ in terms of their modelling structure and input assumptions and, in particular, on the evolution of policy in the coming decades. For example, the IEA’s World Energy Outlook 2006 reference case (IEA, 2006a) and the the International Energy Outlook of the Energy Information Agency in the USA reference case (EIA, 2006b) have both developed sets of scenarios; however, all of these scenarios project a continued dependence on fossil fuels (see Chapter 4 for past global energy mixes and future energy demand and supply projections). Should there be no change in energy policies, the energy mix supplied to run the global economy in the 2025–2030 time frame will essentially remain unchanged with about 80% (IEA, 2006a) of the energy supply based on fossil fuels. In other words, the energy economy may evolve, but not radically change unless policies change. According to the IEA and EIA projections, coal (1.8–2.5% per year), oil (1.3–1.4% per year) and natural gas (2.0–2.4% per year) all continue to grow in the period up to 2030. Among the non-fossil fuels, nuclear (0.7–1.0% per year), hydro (2.0% per year), biomass and waste, including non-commercial biomass (1.3% per year), and other renewables (6.6% per year)13 also continue to grow over the projection period. The growth of new renewables, while robust, starts from a relatively small base. Sectoral growth in energy demand is principally in the electricity generation and transport sectors, and together these will account for 67% of the increase in global energy demand up to 2030 (IEA 2006a). 1.3.2.2
CO2 emissions
Global growth in fossil fuel demand has a significant effect on the growth of energy-related CO2 emissions: both the IEA and the U.S. EIA project growth of more than 55% in their respective forecast periods. The IEA projects a 1.7% per year
13 EIA reports only an aggregate annual growth rate for all renewables of about 2.4% per year.
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growth rate to 2030, while the U.S. EIA projects a 2.0% per year rate in the absence of additional policies. According to IEA projections, emissions will reach 40.4 GtCO2 in 2030, an increase of 14.3 GtCO2 over the 2004 level. SRES14 (IPCC, 2000a) CO2 emissions from energy use for 2030 are in the range 37.2–53.6 GtCO2, which is similar to the levels projected in the EMF-2115 (EMF, 2004) scenarios reviewed in Chapter 3, Section 3.2.2 (35.9–52.1 GtCO2). Relative to the approximately 25.5 GtCO2 emissions in 2000 (see Fig 1.1), fossil fuel-sourced CO2 emissions are projected to increase by 40–110% by 2030 in the absence of climate policies in these scenarios (see Figure 1.7). As the bulk of the growing energy demand occurs in developing countries, the CO2 emission growth accordingly is dominated by developing countries. The latter would contribute two thirds to three quarters of the IEA-projected increase in global energy-related emissions. Developing countries, which accounted for 40% of total fossil fuel-related CO2 emissions in 2004, are projected to overtake the Organization for Economic Co-operation and Development (OECD) as the leading contributor to global CO2 fossil fuel emissions in the early part of the next decade. The CO2 emission projections account for both growth in energy demand and changes in the fuel mix. The IEA projects the share of total energy-related emissions accounted for by gas to increase from 20% in 2004 to 22% in 2030, while the share of coal increases from 41% to 43% and oil drops by approximately 4%, from 39% to 35%, respectively, of the total. On the basis of sectoral shares at the global level, power generation grows from a 41% to a 44% share, while the 20% share of transport is unchanged. The fastest emissions growth rate is in power generation – at 2.0% per year – followed by transport at 1.7% per year. The industry sector grows at 1.6% per year, the residential/commercial sector at 1% per year and international marine and aviation emissions at 0.7% per year. The SRES range of energy-related CO2 emissions for 2100 is much larger, 15.8–111.2 GtCO2, while the EMF-21 scenario range for 2100 is 53.6–101.4 GtCO2. 1.3.2.3
Non- CO2 gases
Methane. Atmospheric CH4 concentrations have increased throughout most of the 20th century, but growth rates have been close to zero over the 1999–2005 period (Solomon et al., 2007; 2.1.1) due to relatively constant emissions during this period equaling atmospheric removal rates (Solomon et al., 2007; 2.1.1). Human emissions continue to dominate the total CH4 emissions budget (Solomon et al., 2007; 7.4.1). Agriculture and forestry developments are assessed in Chapters 8 and 9,
respectively, in terms of their impact on the CH4 sink/source balance and mitigation strategies; waste handling is likewise assessed in Chapter 10. The future increase in CH4 concentrations up to 2030 according to the SRES scenarios ranges from 8.1 GtCO2-eq to 10.3 GtCO2-eq (increase of 19–51% compared to 2000), and the increase under the Energy Modeling Forum (EMF)-21 baseline scenarios is quite similar (7.5 GtCO2-eq to 11.3 GtCO2-eq/yr). By 2100, the projected SRES increase in CH4 concentrations ranges from 5 GtCO2-eq to 18.7 GtCO2-eq (a change of –27% to +175% compared to 2000) and that of the EMF-21 ranges from 5.9 to 29.2 GtCO2-eq (a change of –2% to +390%). Montreal gases. Emissions of ODS gases (also GHGs) controlled under the Montreal Protocol (CFCs, HCFCs) increased from a very low amount during the 1950–1960s to a substantial percentage – approximately 20% – of total GHG emissions by 1975. This percentage fluctuated slightly during the period between 1975 and 1989, but once the phase-out of CFCs was implemented, the ODS share in total GHG emissions fell rapidly, first to 8% (1995) and then to 4% (2000). Radiative forcing from these gases peaked in 2003 and is beginning to decline (Forster et al., 2007). After 2000, ODS contributed 3–4% to total GHG emissions (Olivier et al., 2005, 2006). The ODS share is projected to decrease yet further due to the CFC phase-out in developing countries. Emissions of ODS are estimated at 0.5–1.15 Gt CO2eq for the year 2015, dependent on the scenario chosen (IPCC, 2005); this would be about 1–2% of total GHG emissions for the year 2015, if emissions of all other GHGs are estimated at about 55 Gt CO2-eq (for the year 2015). The percentage of HCFC emissions in the total of CFC and HCFC emissions for the year 2015 is projected to be about 70%, independent of the scenario chosen. Nitrous oxide. Atmospheric concentrations of N2O have been continuously increasing at an approximately constant growth rate since 1980 (IPCC, 2007a, SPM). Industrial sources, agriculture, forestry and waste developments are assessed in this report in terms of their impact on the N2O sink/source balance and mitigation strategies. The SRES emissions for 2030 range from 3 GtCO2-eq to 5.3 GtCO2-eq (a change of –13% to 55% compared to 2000). For comparison, the recent EMF-21 baseline range for 2030 is quite close to this (2.8 GtCO2-eq to 5.4 GtCO2-eq, an increase of –17% to 58% compared to 2000). By 2100, the range projected by the SRES scenarios is 2.6 GtCO2-eq to 8.1 GtCO2-eq (an increase of –23% to 140% compared to 2000), whereas the EMF-21 range is a little higher (3.2 GtCO2-eq to 11.5 GtCO2-eq, or an increase of –5% to 240% compared to 2000).
14 SRES is the IPCC Special Report on Emissions Scenarios (IPCC, 2000a). The ranges reported here are for the five SRES Marker scenarios. 15 EMF-21 Energy Modeling Forum Study 21: Multi-gas Mitigation scenarios (EMF, 2004)
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180
Gt CO2-eq/yr F-gases
160
N2O
140 120
CH4
100
CO2
80 60 40
SRES 2030
post SRES
2100
5th
25th
median
95th
SRES
75th
B1
A1T
B2
A1B
A2
A1FI
5th
25th
median
75th
B2
95th
B1
A1T
A2
A1B
A1FI
0
2000
20
post SRES
Figure 1.7 Global GHG emissions for 2000 and projected baseline emissions for 2030 and 2100 from IPCC SRES and the post-SRES literature. The figure provides the emissions from the six illustrative SRES scenarios. It also provides the frequency distribution of the emissions in the post-SRES scenarios (5th, 25th, median, 75th, 95th percentile), as covered in Chapter 3. F-gases include HFCs, PFCs and SF6
Fluorinated gases. Concentrations of many of these gases have increased by large factors (i.e., 1.3 and 4.3) between 1998 and 2005, and their radiative forcing is rapidly increasing (from low levels) by roughly 10% per year (Forster et al., 2007). Any projection of overall environmental impacts and emissions is complicated by the fact that several major applications retain the bulk of their fluorinated gases during their respective life cycles, resulting in the accumulation of significant stocks that need to be responsibly managed when these applications are eventually decommissioned. A comprehensive review of such assessments was published in an earlier IPCC Special Report (IPCC, 2005). This review reported growth in HFC emissions from about 0.4 GtCO2-eq in 2002 to 1.2 GtCO2-eq per year in 2015. Chapter 3 also describes in some detail the results of long-term GHG emissions scenarios. The range projected by SRES scenarios for 2030 is 1.0–1.6 GtCO2-eq (increase of 190– 360% compared to 2000) and the EMF-21 baseline scenarios are quite close to this (1.2–1.7 GtCO2-eq per year, an increase of 115–240% compared to 2000). By 2100, the SRES range is 1.4–4 GtCO2-eq per year (an increase of 300% to more than 1000 % compared to 2000), whereas the new EMF-21 baseline scenarios are higher still (1.9–6.3 GtCO2-eq).
radiative forcing. There has been a slowing in the growth of sulphur emissions in recent decades, and more recent emission scenarios show lower emissions than earlier ones (Chapter 3, Section 3.2.2). Other air pollutants, such as NOx and black and organic carbon, are also important climatologically and adversely affect human health. The likely future development of these emissions is described in Section 3.2.2.
Air pollutants and other radiative substances. As noted above, some air pollutants, such as sulphur aerosol, have a significant effect on the climate system, although considerable uncertainties still surround the estimates of anthropogenic aerosol emissions. Data on non-sulphur aerosols are sparse and highly speculative, but in terms of global sulphur emissions, these appear to have declined from a range of 75 ± 10 MtS in 1990 to 55–62 MtS in 2000. Sulphur emissions from fossil fuel combustion lead to the formation of aerosols that affect regional climate and precipitation patterns and also reduce
By 2100, the range in the GHG emission projections is much wider from a 40% reduction to an increase of 250% compared to 2000. Scenarios that account for climate policies currently under discussion for implementation also show global emissions rising for many decades. With the atmospheric concentrations of GHGs thus unlikely to stabilize in this century (even for the low SRES scenario) without major policy changes, from an emissions perspective, we are not on track for meeting the objectives of UNFCCC Article 2.
1.3.2.4
Total GHG emissions
Without additional policies global GHG emissions (including those from deforestation) are projected to increase between 25% and 90% by 2030 relative to 2000 (see Figure 1.7). Fossil fuel dominance is expected to continue up to 2030 and beyond; consequently, CO2 emissions from energy use tend to grow faster than total GHGs, increasing by 1.2–2.5% over that period. Two thirds to three quarters of the increase in CO2 emissions are projected to come from developing countries, although the average per capita CO2 emissions in developing country regions will remain substantially lower (2.8– 5.1 tCO2 per capita) than those in developed country regions (9.6–15.1 tCO2 per capita).
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1.3.3
1.3.3.1
Chapter 1
Technology research, development and deployment: needs and trends Research and development
Technology research and development (R&D) are important for altering the emission trends shown in the previous sections. In the absence of measures fostering the development of climate-friendly technologies and/or a lack of incentives for their deployment, however, it is not a priori obvious in which direction R&D will influence emissions. Because of the longevity of energy infrastructures (lock-in effect), it is the near-term investment decisions in the development, deployment and diffusion of technologies that will determine the long-term development of the energy system and its emissions (Gritsevskyi and Nakicenovic, 2002).
response from the latest price surges. A technology R&D response to the challenge of climate mitigation has not occurred. Energy technology R&D has remained roughly constant over the last 15 years despite the fact that climate change has become a focus of international policy development. Energy technology R&D is one policy lever that governments have for encouraging a more climate friendly capital, a strengthened publicly funded commitment to technology development could play an important role in altering the trends in GHG emissions. International cooperation in the field of technology R&D may provide the leverage to otherwise insufficient national R&D budgets. Several international partnerships on the development of cleaner technologies have been created (see Section 1.4.2).
1.4 Generally speaking, it would be economically impossible without technology research, development, demonstration, deployment and diffusion (RDDD&D) and induced technology change (ITC), to stabilize GHG concentrations at a level that would prevent dangerous anthropogenic interference with the climate system. Government support is crucial at the development stage, but private investment will gradually replace the former for deployment (creating necessary market transformation) and for diffusion (successful market penetration). However, RDDD&D alone is insufficient and effective climate policies are also required (Baker et al., 2006). A recent international modelling comparison exercise (Edenhofer et al., 2006) has shown that ITC not only has the potential to reduce mitigation costs substantially but that it is also essential to the stabilization of concentration levels of CO2, avoiding dangerous anthropogenic interference. There are various types of technologies that can play significant roles in mitigating climate change, including energy efficiency improvements throughout the energy system (especially at the end use side); solar, wind, nuclear fission and fusion and geothermal, biomass and clean fossil technologies, including carbon capture and storage; energy from waste; hydrogen production from non-fossil energy sources and fuel cells (Pacala and Socolow, 2004; IEA, 2006b). Some are in their infancy and require public RDDD&D support, while others are more mature and need only market incentives for their deployment and diffusion. Some also need persevering efforts for public acceptance (Tokushige et al., 2006) as well as the resolution of legal and liability issues. 1.3.3.2
Research and development expenditures
The most rapid growth in public-sector energy related technology R&D16 occurred in the aftermath of the oil price shocks of the 1970s. There is no evidence yet of a similar 16 Data for IEA member countries only.
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Institutional architecture
The institutional architecture for climate change, energy and sustainable development in principal covers a wide range of different entities and processes. At the international level, these include the Millennium Development Goals, the World Summit on Sustainable Development in 2002 and its Johannesburg Plan for Implementation (JPOI) and the UN Commission on Sustainable Development (CSD), all of which have broad and important connections to climate change in the context of sustainable development, energy and poverty eradication. Other international fora that are important to advancing the agenda for sustainable development and climate change include – but are not limited to – the UN General Assembly, the G8 Dialogue on Climate Change, Clean Energy and Sustainable Development, OECD, the World Trade Organization (WTO; which pursues trade liberalization, important for technology transfers), IEA and the World Bank. More regional fora include regional banks, the EU and the Asia-Pacific Partnership on Clean Development and Climate for transferring and deploying clean technologies and building up human and institutional capacity. Chapter 2.1 discusses these issues in detail, and they are further evaluated in Chapter 12. This chapter focuses specifically on the UNFCCC and its Kyoto Protocol and with technology cooperation and transfer. 1.4.1
UNFCCC and its Kyoto Protocol
The UNFCCC pursues its ultimate objective, Article 2 (Section 1.2.1), on the basis of several guiding principles laid down in Article 3 of the Convention: • Equity, which is expressed as “common but differentiated responsibilities” that assigns the lead in mitigation to developed countries (Article 3.1) and that takes the needs and special circumstances of developing countries into account (Article 3.2). • A precautionary principle, which says that “where there are
Chapter 1
threats of serious or irreversible damage, lack of full scientific certainty should not be used as a reason for postponing such measures, taking into account that policies and measures to deal with climate change should be cost-effective so as to ensure global benefits at the lowest possible cost” (Article 3.3). • A right to and an obligation to promote sustainable development (Article 3.4). • An obligation to cooperate in sharing information about climate change, technologies through technology transfers, and the coordination of national actions (Article 3.7) Based on the principle of common but differentiated responsibilities, Annex I countries are committed to adopt policies and measures aimed at returning – individually or jointly – their GHG emissions to earlier levels by the year 2000 (Article 4.2). Following the decision of the first Conference of the Parties17 (COP1) in Berlin in 1995 that these commitments were inadequate, the Kyoto Protocol was negotiated and adopted by consensus at COP3, in Kyoto in 1997, and entered into force on 16 February 2005. This was preceded by the detailed negotiation of the implementing rules and agreements for the Protocol – the Marrakech Accords – that were concluded at COP7 in Marrakech and adopted in Montreal at CMP118. As of December 2006, the Protocol has been ratified by 165 countries. While Australia and the United States, both parties to UNFCCC, signed the protocol, both have stated an intention not to ratify. Several key features of the Protocol are relevant to the issues raised later in this report: • Each Party listed in Annex B of the Protocol is assigned a legally binding quantified GHG emission limitation and/or reduction measured in CO2 equivalents for the first commitment period 2008–2012. In aggregate, these Parties are expected to reduce their overall GHG emissions by “at least 5 per cent below 1990 levels in the commitment period 2008 to 2012” (Article 3.1). Some flexibility is shown towards economies in transition who may nominate a base year or period other than 1990 (Article 3.5, 3.7). • Six classes of gases are listed in Annex A of the Protocol: CO2, CH4, N2O, HFCs, PFCs and SF6. Emissions from international aviation and maritime transport are not included. • The so-called Kyoto flexibility mechanisms allow Annex B Parties to obtain emission allowances achieved outside their national borders but supplemental to domestic action, which is expected to be a “significant element of the effort” (Article 6.1 (d), Article17, CMP119). These mechanisms are: an international emission trading system, Joint Implementation (JI) projects in Economies in Transition, projects undertaken as of year 2000 in developing (non-Annex I) countries
Introduction
under the Clean Development Mechanism (CDM) and carbon sink projects in Annex B countries. • A set of procedures for emission monitoring, reporting, verification and compliance has been adopted at CMP1 under Articles 5, 7, 8 and 18. In accordance with Article 3.9, the Parties to the Protocol at CMP1 began the process of negotiating commitments for the Annex B Parties for the second commitment period, creating – the ‘Ad Hoc Working Group on Further Commitments for Annex I Parties under the Kyoto Protocol’ (AWG), with the requirement that negotiations be completed so that that the first and second commitment periods are contiguous. Work continued at CMP2 in Nairobi and in 2007 the AWG will work on, amongst other thing, ranges of emission reduction objectives of Annex I Parties with due attention to the conditions mentioned in Article 2 of the Convention (see 1.2.1). The task is to consider that “according to the scenarios of the TAR, global emissions of carbon dioxide have to be reduced to very low levels, well below half of levels in 2000, in order to stabilize their concentrations in the atmosphere” (see Chapters 3 and 13). In addition, CMP2 started preparations for the second review of the Protocol under Article 9, which in principle covers all aspects of the Protocol, and set 2008 as the date for this review. Under the UNFCCC, a Dialogue on Long-Term Cooperation Action to Address Climate Change by Enhancing Implementation of the Convention (the Dialogue) was established at COP11 in 2005, met during 2006 and is to conclude at COP13 in 2007. The Dialogue is “without prejudice to any future negotiations, commitments, process, framework or mandate under the Convention, to exchange experiences and analyse strategic approaches for long-term cooperative action to address climate change”. 1.4.2
Technology cooperation and transfer
Effective and efficient mitigation of climate change depends on the rate of global diffusion and transfer of new as well as existing technologies. To share information and development costs, international cooperation initiatives for RDDD&D, such as the Carbon Sequestration Leadership Forum (CSLF), the International Partnership for Hydrogen Economy (IPHE), the Generation IV International Forum (GIF), the Methane to Markets Partnership and the Renewable Energy & Energy Efficiency Partnership (REEEP), the Global Bioenergy Partnership and the ITER fusion project, were undertaken. Their mandates range from basic R&D and market demonstration to barrier removals for commercialization/diffusion. In addition,
17 The Conference of the Parties (COP), which is the supreme body of the Convention, also serves as the Meeting of the Parties (MOP) for the Protocol. Parties to the Convention that are not Parties to the Protocol will be able to participate in Protocol-related meetings as observers (Article 13). 18 CMP1: First meeting of the Conference of the Parties acting as the Meeting of the Parties of the Kyoto Protocol. 19 Decisions can be found at http://unfccc.int/documentation/decisions/items/3597.php?dec=j&such=j&volltext=/CMP.1#beg
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there are 40 ‘implementing agreements’ facilitating international cooperation on RDDD&D under IEA auspices, covering all of the key new technologies of energy supply and end use with the exception of nuclear fission (IEA, 2005). Regional cooperation may be effective as well. Asia-Pacific Partnership of Clean Development and Climate (APPCDC), which was established by Australia, China, India, Japan, Korea and the USA in January 2006, aims to address increased energy needs and associated challenges, including air pollution, energy security, and climate change, by enhancing the development, deployment and transfer of cleaner, more efficient technologies. In September 2005, the EU concluded agreements with India and China, respectively, with the aim of promoting the development of cleaner technologies (India) and low carbon technologies (China). Bilateral sector-based cooperation agreements also exist. One example is the Japan/China agreement on energy efficiency in the steel industry, concluded in July 2005 (JISF, 2005). These sector-based initiatives may be an effective tool for technology transfer and mitigating GHG emissions. It is expected that CDM and JI under the Kyoto Protocol will play important role for technology transfer as well.
1.5 Changes from previous assessments and roadmap
Chapter 1
For the Third Assessment Report (TAR) (IPCC, 2001), Working Groups II and III were again reorganized to deal with adaptation and mitigation, respectively. The concept of mitigative capacity was introduced, and the focus attention was shifted to sustainability concerns (IPCC, 2001, Chapter 1.1). Four cross-cutting issues were identified: costing methods, uncertainties, decision analysis frameworks and development, equity and sustainability (IPCC, 2000b). The Fourth Assessment Report (AR4) summarizes the information contained in previous IPCC reports - including the IPCC special reports on Carbon Dioxide Capture and Storage, on Safeguarding the Ozone Layer and on the Global Climate System published since TAR - and assesses the scientific literature published since 2000. Although the structure of AR4 resembles the macro-outline of the TAR, there are distinct differences between them. The AR4 assigns greater weight to (1) a more detailed resolution of sectoral mitigation options and costs; (2) regional differentiation; (3) emphasizing previous and new cross-cutting issues, such as risks and uncertainties, decision- and policy-making, costs and potentials and the relationships between mitigation, adaptation and sustainable development, air pollution and climate, regional aspects and the issues related to the implementation of UNFCCC Article 2; and (4) the integration of all these aspects. 1.5.2
Roadmap
This report assesses options for mitigating climate change. It has four major parts, A–D. 1.5.1
Previous assessments
The IPCC was set up in 1988 by UNEP and WMO with three working groups: to assess available scientific information on climate change (WGI), to assess environmental and socioeconomic impacts (WGII) and to formulate response strategies (WGIII). The First Assessment Report (FAR) (IPCC, 1991) dealt with the anthropogenic alteration of the climate system through CO2 emissions, potential impacts and available cost-effective response measures in terms of mitigation, mainly in the form of carbon taxes without much concern for equity issues (IPCC, 2001, Chapter 1). For the Second Assessment Report (SAR), in 1996, Working Groups II and III were reorganized (IPCC, 1996). WGII dealt with adaptation and mitigation, and WGIII dealt with the socio-economic cross-cutting issues related to costing climate change’s impacts and providing cost-benefit analysis (CBA) for use in decision-making. The socio-institutional context was emphasized as well as the issues of equity, development, and sustainability (IPCC, 2001, Chapter 1).
Part A comprises Chapter 1, an Introduction and Chapter 2, which is on ‘framing issues’. Chapter 2 introduces the report’s cross-cutting themes, which are listed above, and outlines how these themes are treated in subsequent chapters. It also introduces important concepts (e.g. cost-benefit analysis and regional integration) and defines important terms used throughout the report. Part B consists of one chapter, Chapter 3. This chapter reviews and analyzes baseline (non-mitigation) and stabilization scenarios in the literature that have appeared since the publications of the IPCC SRES and the TAR. It pays particular attention to the literature that criticizes the IPCC SRES scenarios and concludes that uncertainties and baseline emissions have not changed very much. It discusses the driving forces for GHG emissions and mitigation in the short and medium terms and emphasizes the role of technology relative to social, economic and institutional inertia. It also examines the relation between adaptation, mitigation and avoided climate change damage in the light of decision-making on atmospheric GHG concentrations (Article 2 UNFCCC). Part C consists of seven chapters, each of which assesses sequence mitigation options in different sectors. Chapter 4
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addresses the energy supply sector, including carbon capture and storage; Chapter 5 transport and associated infrastructures; Chapter 6 the residential, commercial and service sectors; Chapter 7 the industrial sector, including internal recycling and the reuse of industrial wastes; Chapters 8 and 9 the agricultural and forestry sectors, respectively, including land use and biological carbon sequestration; Chapter 10 waste management, post-consumer recycling and reuse. These seven chapters use a common template and cover all relevant aspects of GHG mitigation, including costs, mitigation potentials, policies, technology development, technology transfer, mitigation aspects of the three dimensions of sustainable development, system changes and long-term options. They provide the integrated picture that was absent in the TAR. Where supporting literature is available, they address important differences across regions. Part D comprises three chapters (11–13) that focus on major cross-sectoral considerations. Chapter 11 assesses the aggregated short-/medium-term mitigation potential, macro-economic impacts, economic instruments, technology development and transfer and cross-border influences (or spill-over effects). Chapter 12 links climate mitigation with sustainable development and assesses the GHG emission impacts of implementing the Millennium Development Goals and other sustainable development policies and targets. Chapter 13 assesses domestic climate policy instruments and the interaction between domestic climate policies and various forms of international cooperation and reviews climate change as a global common issue in the context of sustainable development objectives and policies. It summarizes relevant treaties, cooperative development agreements, private–public partnerships and private sector initiatives and their relationship to climate objectives.
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2 Framing Issues Coordinating Lead Authors: Kirsten Halsnæs (Denmark), Priyadarshi Shukla (India)
Lead Authors: Dilip Ahuja (India), Grace Akumu (Kenya), Roger Beale (Australia), Jae Edmonds (USA), Christian Gollier (Belgium), Arnulf Grübler (Austria), Minh Ha Duong (France), Anil Markandya (UK), Mack McFarland (USA), Elena Nikitina (Russia), Taishi Sugiyama (Japan), Arturo Villavicencio (Equador), Ji Zou (PR China)
Contributing Authors: Terry Barker (UK), Leon Clarke (USA), Amit Garg (India)
Review Editors: Ismail Elgizouli (Sudan), Elizabeth Malone (USA)
This chapter should be cited as: Halsnæs, K., P. Shukla, D. Ahuja, G. Akumu, R. Beale, J. Edmonds, C. Gollier, A. Grübler, M. Ha Duong, A. Markandya, M. McFarland, E. Nikitina, T. Sugiyama, A. Villavicencio, J. Zou, 2007: Framing issues. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O. R. Davidson, P. R. Bosch, R. Dave, L. A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA
Framing Issues
Chapter 2
Table of Contents Executive Summary .................................................. 119 2.1
Climate change and Sustainable Development ..................................................... 121 2.1.1
Introduction......................................................121
2.1.2
Background .....................................................121
2.1.3
The dual relationship between climate change and Sustainable Development .........................121
2.1.4
The Sustainable Development concept .............122
2.1.5
Development paradigms ..................................123
2.1.6
International frameworks for evaluating Sustainable Development and climate change links ................................................................124
2.1.7
2.2
2.3
2.4
118
2.5
2.6
Implementation of Sustainable Development and climate change policies ....................................125
Mitigation, vulnerability and adaptation relationships...................................................... 141 2.5.1
Integrating mitigation and adaptation in a development context – adaptive and mitigative capacities ........................................................141
2.5.2
Mitigation, adaptation and climate change impacts ............................................................142
Distributional and equity aspects ................ 142 2.6.1
Development opportunities and equity ..............143
2.6.2
Uncertainty as a frame for distributional and equity aspects..................................................144
2.6.3
Alternative approaches to social justice ............144
2.6.4
Equity consequences of different policy instruments .....................................................145
2.6.5
Economic efficiency and eventual trade-offs with equity ......................................................147
Decision-making .............................................. 127 2.2.1
The ‘public good’ character of climate change ..127
2.2.2
Long time horizons ...........................................127
2.2.3
Irreversibility and the implications for decision-making ...............................................127
2.2.4
Risk of catastrophic or abrupt change ..............128
2.2.5
Sequential decision-making ..............................128
2.2.6
Dealing with risks and uncertainty in decision-making ..............................................129
2.8
2.2.7
Decision support tools .....................................130
References ................................................................... 161
Risk and uncertainty ...................................... 131 2.3.1
How are risk and uncertainty communicated in this report? ......................................................131
2.3.2
Typologies of risk and uncertainty .....................132
2.3.3
Costs, benefits and uncertainties ......................134
Cost and benefit concepts, including private and social cost perspectives and relationships to other decision-making frameworks ....... 134 2.4.1
Definitions ........................................................134
2.4.2
Major cost determinants ...................................136
2.4.3
Mitigation potentials and related costs .............139
2.7 Technology ......................................................... 147 2.7.1
Technology and climate change ........................148
2.7.2
Technological change .......................................152
2.7.3
The international dimension in technology development and deployment: technology transfer ............................................................158
Regional dimensions ....................................... 160
Chapter 2
Framing Issues
EXECUTIVE SUMMARY This chapter frames climate change mitigation policies in the context of general development issues and recognizes that there is a two-way relationship between climate change and sustainable development. These relationships create a wide potential for linking climate change and sustainable development policies, and an emerging literature has identified methodological approaches and specific policies that can be used to explore synergies and tradeoffs between climate change and economic, social, and environmental sustainability dimensions. Decision-making about climate change policies is a very complex and demanding task since there is no single decisionmaker and different stakeholders assign different values to climate change impacts and to the costs and benefits of policy actions. However, many new initiatives emerge from governmental cooperation efforts, the business sector and NGOs (non-governmental organizations), so various coalitions presently play an increasing role. A large number of analytical approaches can be used to support decision-making, and progress has been made both in integrated assessment models, policy dialogues and other decision support tools. Like most policy-making, climate policy involves trading off risks and uncertainties. Risks and uncertainties have not only natural but also human and social dimensions. They arise from missing, incomplete and imperfect evidence, from voluntary or involuntary limits to information management, from difficulties in incorporating some variables into formal analysis, as well as from the inherently unpredictable elements of complex systems. An increasing international literature considers how the limits of the evidence basis and other sources of uncertainties can be estimated. Costs and benefits of climate change mitigation policies can be assessed (subject to the uncertainties noted above) at project, firm, technology, sectoral, community, regional, national or multinational levels. Inputs can include financial, economic, ecological and social factors. In formal cost-benefit analyses, the discount rate is one major determinant of the present value of costs and benefits, since climate change, and mitigation/ adaptation measures all involve impacts spread over very long time periods. Much of the literature uses constant discount rates at a level estimated to reflect time preference rates as used when assessing typical large investments. Some recent literature also includes recommendations about using timedecreasing discount rates, which reflect uncertainty about future economic growth, fairness and intra-generational distribution, and observed individual choices. Based on this, some countries officially recommend using time-decreasing discount rates for long time horizons. The potential linkages between climate change mitigation and adaptation policies have been explored in an emerging
literature. It is concluded that there is a number of factors that condition societies’ or individual stakeholders’ capacity to implement climate change mitigation and adaptation policies including social, economic, and environmental costs, access to resources, credit, and the decision-making capacity in itself. Climate change has considerable implications for intragenerational and inter-generational equity, and the application of different equity approaches has major implications for policy recommendations, as well as for the implied distribution of costs and benefits of climate policies. Different approaches to social justice can be applied when evaluating equity consequences of climate change policies. They span traditional economic approaches where equity appears in terms of the aggregated welfare consequences of adaptation and mitigation policies, and rights-based approaches that argue that social actions are to be judged in relation to the defined rights of individuals. The cost and pace of any response to climate change concerns will critically depend on the social context, as well as the cost, performance, and availability of technologies. Technological change is particularly important over the long-term time scales that are characteristic of climate change. Decade (or longer) time scales are typical for the gaps involved between technological innovation and widespread diffusion, and of the capital turnover rates characteristic for long-term energy capital stock and infrastructures. The development and deployment of technology is a dynamic process that arises through the actions of human beings, and different social and economic systems have different proclivities to induce technological change, involving a different set of actors and institutions in each step. The state of technology and technology change, as well as human capital and other resources, can differ significantly from country to country and sector to sector, depending on the starting point of infrastructure, technical capacity, the readiness of markets to provide commercial opportunities and policy frameworks.
The climate change mitigation framing issues in general are characterized by high agreement/much evidence relating to the range of theoretical and methodological issues that are relevant in assessing mitigation options. Sustainable development and climate change, mitigation and adaptation relationships, and equity consequences of mitigation policies are areas where there is conceptual agreement on the range of possible approaches, but relatively few lessons can be learned from studies, since these are still limited (high agreement, limited evidence). Other issues, such as mitigation cost concepts and technological change are very mature in the mitigation policy literature, and there is high agreement/much evidence relating to theory, modelling, and other applications. In the same way, decision-making approaches and various tools and approaches are characterized by high agreement on the range of conceptual issues (high agreement, much evidence), but there is significant divergence in the applications, primarily since some approaches have been applied widely and others have only been applied to 119
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a more limited extent (high agreement, limited evidence). There is some debate about which of these framing methodologies and issues relating to mitigation options are most important, reflecting (amongst other things) different ethical choices – to this extent at least there is an irreducible level of uncertainty (high agreement, limited evidence).
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2.1 Climate change and Sustainable Development 2.1.1
Introduction
This section introduces the relationship between sustainable development (SD) and climate change and presents a number of key concepts that can be used to frame studies of these relationships. Climate change and sustainable development are considered in several places throughout this report. Chapter 12 provides a general overview of the issues, while more specific issues relating to short- and long-term mitigation issues are addressed in Chapters 3 (Section 3.1) and 11 (Section 11.6). Sectoral issues are covered in Chapters 4-10 (Sections 4.5.4, 5.5.5, 6.9.2, 7.7, 8.4.5, 9.7, and in 10.6). Furthermore, the IPCC (2007b) addresses SD and climate change in Chapters 18 and 20. 2.1.2
Background
The IPCC’s Third Assessment Report (TAR; IPCC, 2001) included considerations concerning SD and climate change. These issues were addressed particularly by Working Group II and III, as well as the Synthesis report. The TAR included a rather broad treatment of SD (Metz et al., 2002). The report noted three broad classes of analyses or perspectives: efficiency and cost-effectiveness, equity and sustainable development, and global sustainability and societal learning. Since the TAR, literature on sustainable development and climate change has attempted to further develop approaches that can be used to assess specific development and climate policy options and choices in this context (Beg et al., 2002; Cohen et al., 1998; Munasinghe and Swart, 2000; Schneider, 2001; Banuri et al., 2001; Halsnæs and Verhagen, 2007; Halsnæs, 2002; Halsnæs and Shukla, 2007, Markandya and Halsnæs, 2002a; Metz et al. 2002; Munasinghe and Swart, 2005; Najam and Rahman, 2003; Smit et al., 2001; Swart et al.,. 2003; Wilbanks, 2003). These have included discussions about how distinctions can be made between natural processes and feedbacks, and human and social interactions that influence the natural systems and that can be influenced by policy choices (Barker, 2003). These choices include immediate and very specific climate policy responses as well as more general policies on development pathways and the capacity for climate change adaptation and mitigation. See also Chapter 12 of this report and Chapter 18 of IPCC (2007b) for a more extensive discussion of these issues. Policies and institutions that focus on development also affect greenhouse gas (GHG) emissions and vulnerability. Moreover, these same policies and institutions constrain or facilitate mitigation and adaptation. These indirect effects can be positive or negative, and several studies have therefore suggested the integration of climate change adaptation and mitigation perspectives into development policies, since sustainable development requires coping with climate change
and thereby will make development more sustainable (Davidson et al., 2003; Munasinghe and Swart, 2005; Halsnæs and Shukla, 2007). Climate change adaptation and mitigation can also be the focus of policy interventions and SD can be considered as an issue that is indirectly influenced. Such climate policies can tend to focus on sectoral policies, projects and policy instruments, which meet the adaptation and mitigation goals, but are not necessarily strongly linked to all the economic, social, and environmental dimensions of sustainable development. In this case climate change policy implementation in practice can encounter some conflicts between general development goals and the goal of protecting the global environment. Furthermore, climate policies that do not take economic and social considerations into account might not be sustainable in the long run. In conclusion, one might then distinguish between climate change policies that emerge as an integrated element of general sustainable development policies, and more specific adaptation and mitigation policies that are selected and assessed primarily in their capacity to address climate change. Examples of the first category of policies can be energy efficiency measures, energy access and affordability, water management systems, and food security options, while examples of more specific adaptation and mitigation policies can be flood control, climate information systems, and the introduction of carbon taxes. It is worth noticing that the impacts on sustainable development and climate change adaptation and mitigation of all these policy examples are very context specific, so it cannot in general be concluded whether a policy supports sustainable development and climate change jointly or if there are serious tradeoffs between economic and social perspectives and climate change (see also Chapter 12 of this report and Chapter 18 of IPCC (2007b) for a more extensive discussion). 2.1.3
The dual relationship between climate change and Sustainable Development
There is a dual relationship between sustainable development and climate change. On the one hand, climate change influences key natural and human living conditions and thereby also the basis for social and economic development, while on the other hand, society’s priorities on sustainable development influence both the GHG emissions that are causing climate change and the vulnerability. Climate policies can be more effective when consistently embedded within broader strategies designed to make national and regional development paths more sustainable. This occurs because the impact of climate variability and change, climate policy responses, and associated socio-economic development will affect the ability of countries to achieve sustainable development goals. Conversely, the pursuit of those goals will in turn affect the opportunities for, and success of, climate policies. 121
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Climate change impacts on development prospects have also been described in an interagency project on poverty and climate change as ‘Climate Change will compound existing poverty. Its adverse impacts will be most striking in the developing nations because of their dependence on natural resources, and their limited capacity to adapt to a changing climate. Within these countries, the poorest, who have the least resources and the least capacity to adapt, are the most vulnerable’ (African Development Bank et al., 2003). Recognizing the dual relationship between SD and climate change points to a need for the exploration of policies that jointly address SD and climate change. A number of international study programmes, including the Development and Climate project (Halsnæs and Verhagen, 2007), and an OECD development and environment directorate programme (Beg et al., 2002) explore the potential of SD-based climate change policies. Other activities include projects by the World Resources Institute (Baumert et al., 2002), and the PEW Centre (Heller and Shukla, 2003). Furthermore, the international literature also includes work by Cohen et al., 1998; Banuri and Weyant, 2001; Munasinghe and Swart 2000; Metz et al., 2002; Munasinghe and Swart, 2005; Schneider et al., 2000; Najam and Rahman, 2003; Smit et al., 2001; Swart et al., 2003; and Wilbanks, 2003). 2.1.4
The Sustainable Development concept
Sustainable development (SD) has been discussed extensively in the theoretical literature since the concept was adopted as an overarching goal of economic and social development by UN agencies, by the Agenda 21 nations, and by many local governments and private-sector actors. The SD literature largely emerged as a reaction to a growing interest in considering the interactions and potential conflicts between economic development and the environment. SD was defined by the World Commission on Environment and Development in the report Our Common Future as ‘development that meets the needs of the present without compromising the ability of future generations to meet their own needs’ (WCED, 1987). The literature includes many alternative theoretical and applied definitions of sustainable development. The theoretical work spans hundreds of studies that are based on economic theory, complex systems approaches, ecological science and other approaches that derive conditions for how development paths can meet SD criteria. Furthermore, the SD literature emphasizes a number of key social justice issues including inter- and intra-generational equity. These issues are dealt with in Section 2.6. Since a comprehensive discussion of the theoretical literature on sustainable development is beyond the scope of this report, a pragmatic approach limits us to consider how development can 1
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be made more sustainable. The debate on sustainability has generated a great deal of research and policy discussion on the meaning, measurability and feasibility of sustainable development. Despite the intrinsic ambiguity in the concept of sustainability, it is now perceived as an irreducible holistic concept where economic, social, and environmental issues are interdependent dimensions that must be approached within a unified framework (Hardi and Barg, 1997; Dresner, 2002; Meadows, 1998). However, the interpretation and valuation of these dimensions have given rise to a diversity of approaches. A growing body of concepts and models, which explores reality from different angles and in a variety of contexts, has emerged in recent years in response to the inability of normal disciplinary science to deal with complexity and systems – the challenges of sustainability. The outlines of this new framework, known under the loose term of ‘Systems Thinking’, are, by their very nature, transdisciplinary and synthetic (Kay and Foster, 1999). An international group of ecologists, economists, social scientists and mathematicians has laid the principles and basis of an integrative theory of systems change (Holling 2001). This new theory is based on the idea that systems of nature and human systems, as well as combined human and nature systems and social-ecological systems, are interlinked in never-ending adaptive cycles of growth, accumulation, restructuring, and renewal within hierarchical structures (Holling et al., 2002). A core element in the economic literature on SD is the focus on growth and the use of man-made, natural, and social capital. The fact that there are three different types of capital that can contribute to economic growth has led to a distinction between weak and strong sustainability, as discussed by Pearce and Turner (1990), and Rennings and Wiggering (1997). Weak sustainability describes a situation where it is assumed that the total capital is maintained and that the three different elements of the capital stock can, to some extent, be used to substitute each other in a sustainable solution. On the other hand, strong sustainability requires each of the three types of capital to be maintained in its own right, at least at some minimum level. An example of an application of the strong sustainability concept is Herman Daly’s criteria, which state that renewable resources must be harvested at (or below) some predetermined stock level, and renewable substitutes must be developed to offset the use of exhaustible resources (Daly, 1990). Furthermore, pollution emissions should be limited to the assimilative capacity of the environment. Arrow et al., 2004, in a joint authorship between leading economists and ecologists, present an approach for evaluating alternative criteria for consumption1, seen over time in a sustainable development perspective. Inter-temporal consumption and utility are introduced here as measurement
Consumption should here be understood in a broad sense as including all sorts of goods that are elements in a social welfare function.
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points for sustainable development. One of the determinants of consumption and utility is the productive base of society, which consists of capital assets such as manufactured capital, human capital, and natural capital. The productive base also includes the knowledge base of society and institutions.
maintenance of essential biophysical life support systems, more universal participation in development processes and decisionmaking, and the achievement of an acceptable standard of human well-being (Swart et al., 2003; Meadowcroft, 1997; WCED, 1987).
Although institutions are often understood as part of the capital assets, Arrow et al. (2004) only consider institutions in their capacity as guiding the allocation of resources, including capital assets. Institutions in this context include the legal structure, formal and informal markets, various government agencies, inter-personal networks, and the rules and norms that guide their behaviour. Seen from an SD perspective, the issue is then: how, and to what extent, can policies and institutional frameworks for these influence the productive basis of society and thereby make development patterns more sustainable.
In the more specific context of climate change policies, the controversy between different sustainability approaches has shown up in relation to discussions on key vulnerabilities; see Section 2.5.2 for more details.
The literature includes other views of capital assets that will consider institutions and sustainable development policies as being part of the social capital element in society’s productive base. Lehtonen (2004) provides an overview of the discussion on social capital and other assets. He concludes that despite capabilities and social capital concepts not yet being at the practical application stage, the concepts can be used as useful metaphors, which can help to structure thoughts across different disciplines. Lehtonen refers to analysis of social-environmental dimensions by the OECD (1998) that addresses aspects such as demography, health, employment, equity, information, training, and a number of governance issues, as an example of a pragmatic approach to including social elements in sustainability studies. Arrow et al., (2004) summarize the controversy between economists and ecologists by saying that ecologists have deemed current consumption patterns to be excessive or deficient in relation to sustainable development, while economists have focused more on the ability of the economy to maintain living standards. It is concluded here that the sustainability criterion implies that inter-temporal welfare should be optimized in order to ensure that current consumption is not excessive.2 However, the optimal level of current consumption cannot be determined (i.e. due to various uncertainties). Theoretical considerations therefore focus instead on factors that make current consumption more or less sustainable. These factors include the relationship between market rates of return on investments and social discount rates, and the relationship between market prices of consumption goods (including capital goods) and the social costs of these commodities. Some basic principles are therefore emerging from the international sustainability literature, which helps to establish commonly held principles of sustainable development. These include, for instance, the welfare of future generations, the
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2.1.5
Development paradigms
Assessment of SD and climate change in the context of this report considers how current development can be made more sustainable. The focus is on how development goals, such as health, education, and energy, food, and water access can be achieved without compromising the global climate. When applying such a pragmatic approach to the concept of SD it is important to recognize that major conceptual understandings and assumptions rely on the underlying development paradigms and analytical approaches that are used in studies. The understanding of development goals and the tradeoffs between different policy objectives depends on the development paradigm applied, and the following section will provide a number of examples on how policy recommendations about SD and climate change depend on alternative understandings of development as such. A large number of the models that have been used for mitigation studies are applications of economic paradigms. Studies that are based on economic theory typically include a specification of a number of goals that are considered as important elements in welfare or human wellbeing. Some economic paradigms focus on the welfare function of the economy, assuming efficient resource allocation (such as in neoclassical economics), and do not consider deviations from this state and ways to overcome these. In terms of analyzing development and climate linkages, this approach will see climate change mitigation as an effort that adds a cost to the optimal economic state.3 However, there is a very rich climate mitigation cost literature that concludes that market imperfections in practice often create a potential for mitigation policies that can help to increase the efficiency of energy markets and thereby generate indirect cost savings that can make mitigation policies economically attractive (IPCC, 1996, Chapters 8 and 9; IPCC, 2001, Chapters 7 and 8). The character of such market imperfections is discussed further in Section 2.4. Other development paradigms based on institutional economics focus more on how markets and other information-
Arrow et al. (2004) state that ‘actual consumption today is excessive if lowering it and increasing investment (or reducing disinvestment) in capital assets could raise future utility enough to more than compensate (even after discounting) for the loss in current utility’. Take the benefits of avoided climate change into consideration.
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sharing mechanisms establish a framework for economic interactions. Recent development research has included studies on the role of institutions as a critical component in an economy’s capacity to use resources optimally. Institutions are understood here in a broad sense, as being a core allocation mechanism and as the structure of society that organizes markets and other information sharing (Peet and Hartwick, 1999).
See also Section 2.6, where the equity dimensions of basic needs and well-being approaches are discussed in more detail.
In this context, climate policy issues can include considerations about how climate change mitigation can be integrated into the institutional structure of an economy. More specifically, such studies can examine various market and nonmarket incentives for different actors to undertake mitigation policies and how institutional capacities for these policies can be strengthened. Furthermore, institutional policies in support of climate change mitigation can also be related to governance and political systems – see a more elaborate discussion in Chapter 12, Section 12.2.3.
The capability approaches taken by Sen and Dasgupta have been extended by some authors from focusing on individuals to also covering societies (Ballet et al., 2003; Lehtonen, 2004). It is argued here that, when designing policies, one needs to look at the effects of economic and environmental policies on the social dimension, including individualistic as well as social capabilities, and that these two elements are not always in harmony.
Weak institutions have a lot of implications for the capacity to adapt or mitigate to climate change, as well as in relation to the implementation of development policies. A review of the social capital literature related to economic aspects and the implications for climate change mitigation policies concludes that, in most cases, successful implementation of GHG emissionreduction options will depend on additional measures to increase the potential market and the number of exchanges. This can involve strengthening the incentives for exchange (prices, capital markets, information efforts etc.), introducing new actors (institutional and human capacity efforts), and reducing the risks of participation (legal framework, information, general policy context of market regulation). All these measures depend on the nature of the formal institutions, the social groups of society, and the interactions between them (Olhoff, 2002). See also Chapter 12 of this report for a more extensive discussion of the political science and sociological literature in this area. Key theoretical contributions to the economic growth and development debate also include work by A. Sen (1999) and P. Dasgupta (1993) concerning capabilities and human wellbeing. Dasgupta, in his inquiry into well-being and destitution, concludes that ‘our citizens’ achievements are the wrong things to look at. We should be looking at the extent to which they enjoy the freedom to achieve their ends, no matter what their ends turn out to be. The problem is that the extent of such freedoms depends upon the degree to which citizens make use of income and basic needs’. (Dasgupta, 1993, pp. 54). Following this, Dasgupta recommends studying the distribution of resources, as opposed to outcomes (which, for example, can be measured in terms of welfare). The access to income and basic needs are seen as a fundamental basis for human well-being and these needs include education, food, energy, medical care etc. that individuals can use as inputs to meeting their individual desires.
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WEHAB stands for Water, Energy, Health, Agriculture, and Biodiversity.
In the context of capabilities and human well-being, climate change policies can then include considerations regarding the extent to which these policies can support the access of individuals to specific resources as well as freedoms.
2.1.6
International frameworks for evaluating Sustainable Development and climate change links
Studies that assess the sustainable development impacts of climate change (and vice versa) when they are considering short to medium-term perspectives will be dealing with a number of key current development challenges. This section provides a short introduction to international policy initiatives and decisions that currently offer a framework for addressing development goals. A key framework that can be used to organize the evaluation of SD and climate change linkages is the WEHAB4 framework that was introduced by the World Summit on Sustainable Development in 2002 (WSSD, 2002). The WEHAB sectors reflect the areas selected by the parties at the WSSD meeting to emphasize that particular actions were needed in order to implement Agenda 21. Seen from a climate change policy evaluation perspective it would be relevant to add a few more sectors to the WEHAB group in order to facilitate a comprehensive coverage of major SD and climate change linkages. These sectors include human settlements tourism, industry, and transportation. It would also be relevant to consider demography, institutions and various cultural issues and values as cross-cutting sectoral issues. Climate change policy aspects can also be linked to the Millennium Development Goals (MDG) that were adopted as major policy targets by the WSSD. The MDGs include nine general goals to eradicate poverty and hunger, health, education, natural resource utilization and preservation, and global partnerships that are formulated for the timeframe up to 2015 (UNDP, 2003a).
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A recent report by the CSD (Commission on Sustainable Development) includes a practical plan for how to achieve the Millennium Development Goals (CSD, 2005). Climate change is explicitly mentioned in the CSD report as a factor that could worsen the situation of the poor and make it more difficult to meet the MDGs. Furthermore, CSD (2005) suggests adding a number of energy goals to the MDGs (i.e. to reflect energy security and the role that energy access can play in poverty alleviation). Adding energy as a separate component in the MDG framework will establish a stronger link between MDGs and climate change mitigation. Several international studies and agency initiatives have assessed how the MDGs can be linked to goals for energy, food-, and water access and to climate change impacts, vulnerability, and adaptation (African Development Bank et al., 2003), and an example of how the link between climate change and MDGs can be further developed to include both adaptation and mitigation is shown in Table 2.1. A linkage between MDGs and development goals is also described very specifically by Shukla (2003) and Shukla et al. (2003) in relation to the official Indian 10th plan for 2002–2007. In the same way, the Millenium Ecosystem Assessment (MEA) presents a global picture of the relationship between the net gains in human well-being and economic development based on a growing cost through degradation of ecosystem services, and demonstrates how this can pose a barrier to achieving the MDGs (MEA, 2005). Measuring progress towards SD requires the development and systematic use of a robust set of indicators and measures. Agenda 21 (1992) explicitly recognizes in Chapter 40 that a pre-requisite for action is the collection of data at various levels (local, provincial, national and international), indicating the status and trends of the planet’s ecosystems, natural resources, pollution and socio-economy. The OECD Ministerial Council decided in 2001 that the regular Economic Surveys of OECD countries should include an evaluation of SD dimensions, and a process for agreeing on SD indicators. These will be used in regular OECD peer reviews of government policies and performance. From the OECD menu of SD issues, the approach is to select a few areas that will be examined in depth, based on specific country relevance (OECD, 2003). The first OECD evaluation of this kind was structured around three topics that member countries could select from the following list of seven policy areas (OECD, 2004): • Improving environmental areas: - Reducing GHG emissions - Reducing air pollutants - Reducing water pollution - Moving towards sustainable use of renewable and nonrenewable natural resources - Reducing and improving waste management
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• Improving living standards in developing countries. • Ensuring sustainable retirement income policies. Most of the attention in the country choice was given to the environmental areas, while evaluation of improving living standards in developing countries was given relatively little attention in this first attempt. The use of SD indicators for policy evaluations has been applied in technical studies of SD and climate change (Munasinghe, 2002; Atkinson et al., 1997; Markandya et al., 2002). These studies address SD dimensions based on a number of economic, environmental, human and social indicators, including both quantitative and qualitative measurement standards. A practical tool applied in several countries, called the Action Impact Matrix (AIM), has been used to identify, prioritize, and address climate and development synergies and tradeoffs (Munasinghe and Swart, 2005). All together, it can be concluded that many international institutions and methodological frameworks offer approaches for measuring various SD dimensions, and that these have been related to broader development and economic policies by CSD, the WSSD, and the OECD. Many indexes and measurement approaches exist but, until now, relatively few studies have measured climate change in the context of these indexes. In this way, there is still a relatively weak link between actual measurements of and climate change links. 2.1.7
Implementation of Sustainable Development and climate change policies
SD and climate change are influenced by a number of key policy decisions related to economic, social and environmental issues, as well as by business-sector initiatives, private households and many other stakeholders, and these decisions are again framed by government policies, markets, information sharing, culture, and a number of other factors. Some of the decisions that are critically important in this context are investments, use of natural resources, energy consumption, land use, technology choice, and consumption and lifestyle, all of which can lead to both increasing and decreasing GHG emission intensities, which again will have implications for the scope of the mitigation challenge. Seen in a longerterm perspective these decisions are critical determinants for development pathways. There has been an evolution in our understanding of how SD and climate change mitigation decisions are taken by societies. In particular, this includes a shift from governments that are defined by the nation/state to a more inclusive concept of governance, which recognizes various levels of government (global, transnational/regional, and local), as well as the roles of the private sector, non-governmental actors and civil society. Chapter 12, Section 12.2.3, includes a comprehensive
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Table 2.1: Relationship between MDGs, energy-, food-, and water access, and climate change MDG goals To halve (between 1990 and 2015), the proportion of the world’s population whose income is below 1US$ a day
To reduce by two-thirds (between 1990 and 2015), the death rate for children under the age of five years
To reduce by three-quarters (between 1990 and 2015) the rate of maternal mortality
Combat HIV/AIDS, malaria and other major diseases
To stop the unsustainable exploitation of natural resources
To halve (between 1990 and 2015), the proportion of people who are unable to reach and afford safe drinking water
Sectoral themes Energy: Energy for local enterprises Lighting to facilitate income generation Energy for machinery Employment related to energy provision
Climate change links Energy: GHG emissions. Adaptive and mitigative capacity increase due to higher income levels and decreased dependence on natural resources, production costs etc.
Food/water: Increased food production Improved water supply Employment
Food/water: GHG emissions Increased productivity of agriculture can reduce climate change vulnerability. Improved water management and effective use can help adaptation and mitigation. Increased water needs for energy production Energy: GHG emissions
Energy: Energy supply can support health clinics Reduced air pollution from traditional fuels Reduced time spent on fuel collection can increase the time spent on children’s health care Food/water: Improved health due to increased supply of highquality food and clean water Reduced time spent on food and water provision can increase the time spent on children’s health care Improved waste and wastewater treatment Energy: Energy provision for health clinics Reduced air pollution from traditional fuels and other health improvements.
Food/water: Health improvements will decrease vulnerability to climate change and the adaptive capacity Decreased methane and nitrous oxide emissions
Food/water: Improved health due to increased supply of highquality food and clean water Time savings on food and water provision can increase the time spent on children’s health care Energy: Energy for health clinics Cooling of vaccines and medicine
Food/water: Health improvements will decrease vulnerability to climate change and the adaptive capacity
Food/water: Health improvements from cleaner water supply Food production practices that reduce malaria potential
Food/water: Health improvements will decrease vulnerability to climate change and the adaptive capacity
Energy: Deforestation caused by woodfuel collection Use of exhaustible resources
Energy: GHG emissions Carbon sequestration
Food/water: Land degradation
Food/water: Carbon sequestration Improved production conditions for landuse activities will increase the adaptive and mitigative capacity Energy: GHG emissions
Energy: Energy for pumping and distribution systems, and for desalination and water treatment Water: Improved water systems
Source: based on Davidson et al., (2003).
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Energy: GHG emissions
Energy: GHG emissions from increased health clinic services, but health improvements can also reduce the health service demand
Water: Reduced vulnerability and enhanced adaptive capacity
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assessment of how state, market, civil society and partnerships play a role in sustainable development and climate change policies.
2.2 2.2.1
Decision-making
The ‘public good’ character of climate change
Mitigation costs are exclusive to the extent that they may be borne by some individuals (nations) while others might evade them (free-riding) or might actually gain a trade/investment benefit from not acting (carbon leakage). The incentive to evade taking mitigation action increases with the substitutability of individual mitigation efforts and with the inequality of the distribution of net benefits. However, individual mitigation efforts (costs) decrease with efficient mitigation actions undertaken by others. The unequal distribution of climate benefits from mitigation action, of the marginal costs of mitigation action and of the ability to pay emission reduction costs raises equity issues and increases the difficulty of securing agreement. In a strategic environment, leadership from a significant GHG emitter may provide an incentive for others to follow suit by lowering their costs (Grasso, 2004; ODS, 2002). Additional understandings come from political science, which emphasizes the importance of analyzing the full range of factors that have a bearing on decisions by nation states, including domestic pressures from the public and affected interest groups, the role of norms and the contribution of NGOs to the negotiation processes. Case studies of many MEAs (Multilateral Environmental Agreements) have provided insights, particularly on the institutional, cultural, political and historical dimensions that influence outcomes (Cairncross, 2004). A weakness of this approach is that the conclusions can differ depending on the choice of cases and the way in which the analysis is implemented. However, such ex-post analysis of the relevant policies often provides deep insights that are more accessible to policymakers, rather than theoretical thinking or numeric models. 2.2.2
Long time horizons
Climate policy raises questions of inter-generational equity and changing preferences, which inevitably affect the social weighting of environmental and economic outcomes, due to the long-term character of the impacts (for a survey see Bromley and Paavola, 2002). However, studies traditionally assume that preferences will be stable over the long time frames involved in the assessment of climate policy options. To the extent that no value is
attached to the retention of future options, the preferences of the present generation are implicitly given priority in much of this analysis. As time passes, preferences will be influenced by information, education, social and organizational affiliation, income distribution and a number of cultural values (PalaciosHuerta and Santos, 2002). Institutional frameworks are likely to develop to assist groups, companies and individuals to form preferences in relation to climate change policy options. The institutions can include provision of information and general education programmes, research and assessments, and various frameworks that can facilitate collective decision-making that recognizes the common ‘global good’ character of climate change. At an analytic level, the choice of discount rates can have a profound affect on valuation outcomes – this is an important issue in its own right and is discussed in Section 2.4.1. 2.2.3
Irreversibility and the implications for decision-making
Human impacts on the climate system through greenhouse gas emissions may change the climate so much that it is impossible (or extremely difficult and costly) to return it to its original state – in this sense the changes are irreversible (Scheffer et al., 2001; Schneider, 2004). Some irreversibility will almost certainly occur. For example, there is a quasi-certain irreversibility of a millennia time scale in the presence, in the atmosphere, of 22% of the emitted CO2 (Solomon et al., 2007). However, the speed and nature of these changes, the tipping point at which change may accelerate and when environmentally, socially and economically significant effects become irreversible, and the cost and effectiveness of mitigation and adaptation responses are all uncertain, to a greater or lesser extent. The combination of environmental irreversibility, together with these uncertainties (Baker, 2005; Narain et al., 2004; Webster, 2002; Epstein, 1980) means that decision-makers have to think carefully about: a) The timing and sequencing of decisions to preserve options. b) The opportunity to sequence decisions to allow for learning about climate science, technology development and social factors (Baker, 2005; Kansuntisukmongko, 2004). c) Whether the damage caused by increases in greenhouse concentrations in the atmosphere will increase proportionally and gradually or whether there is a risk of sudden, nonlinear changes, and similarly whether the costs of reducing emissions change uniformly with time and the depth of reduction required, or are they possibly subject to thresholds or other non-linear effects. d) Whether the irreversible damages are clustered in particular parts of the world or have a general effect, and e) whether there is a potential that these irreversible damages will be catastrophically severe for some, many or even all communities (Cline, 2005). 127
Framing Issues
Just as there are risks of irreversible climate changes, decisions to reduce GHG emissions can require actions that are essentially irreversible. For example, once made, these longlived, large-scale investments in low-emission technologies are irreversible. If the assumptions about future policies and the directions of climate science on which these investments are made prove to be wrong, they would become ‘stranded’ assets. The risks (perceived by investors) associated with irreversibility of this nature further complicate decision-making on abatement action (Keller et al., 2004; Pindyck, 2002; Kolstad, 1996; Sullivan et al., 2006; Hamilton and Kenber, 2006). Without special actions by governments to overcome their natural inertia, economic and social systems might delay too long in reacting to climate risks, thus leading to irreversible climate changes. Ambitious climate-protection goals would require new investments (physical and intellectual) in climatefriendly technologies (efficiency improvements, renewables, nuclear power, carbon capture and storage), which are higher in cost than current technologies or otherwise divert scarce resources. From an economic point of view these investments are essentially irreversible. As the scale of the investment and the proportion of research and development costs increase, so the private economic risks associated with irreversibility also increase. Therefore, in the presence of uncertainty concerning future policy towards GHG emission reduction, future carbon prices or stabilization targets, investors are reluctant to undertake large-scale irreversible investments (sunk costs) without some form of upfront government support. 2.2.4
Risk of catastrophic or abrupt change
The possibility of abrupt climate change and/or abrupt changes in the earth system triggered by climate change, with potentially catastrophic consequences, cannot be ruled out (Meehl et al., 2007). Disintegration of the West Antarctic Ice Sheet (See Meehl et al., 2007), if it occurred, could raise sea level by 4-6 metres over several centuries. A shutdown of the North Atlantic Thermohaline Circulation (See Meehl et al., 2007) could have far-reaching, adverse ecological and agricultural consequences (See IPCC, 2007b, Chapter 17), although some studies raise the possibility that the isolated, economic costs of this event might not be as high as assumed (See Meehl et al., 2007). Increases in the frequency of droughts (Salinger, 2005) or a higher intensity of tropical cyclones (See Meehl et al., 2007) could occur. Positive feedback from warming may cause the release of carbon or methane from the terrestrial biosphere and oceans (See Meehl et al., 2007), which would add to the mitigation required. Much conventional decision-making analysis is based on the assumption that it is possible to model and compare all the outcomes from the full range of alternative climate policies. It also assumes there is a smooth trade-off between the different dimensions of each policy outcome; that a probability distribution provides an expected value for each 128
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outcome, and that there is a unique best solution – the one with the highest expected value. Consequently, it could suggest that a policy which risked a catastrophically bad outcome with a very low probability might be valued higher than one which completely avoided the possibility of catastrophe and produced merely a bad outcome, but with a very high probability of occurrence. Assumptions that it is always possible to ‘trade off’ more of one dimension (e.g. economic growth) for less of another (e.g. species protection) – that there is always a price at which we are comfortable to ‘dispense with’ a species in the wild (e.g. polar bears), an ecological community or indigenous cultures are problematic for many people. This also applies to assumptions that decision-makers value economic (and other) gains and losses symmetrically – that a dollar gained should always assumed to be valued equally to one that is lost, and that it is possible and appropriate to assume that the current generation’s preferences will remain stable over time. Recent literature drawing on experimental economics and behavioural sciences suggests that these assumptions are an incomplete description of the way in which humans really make decisions. This literature suggests that preferences may be lexicographical (i.e. it is not possible to ‘trade off’ between different dimensions of alternative possible outcomes – there may be an aversion at any ‘price’ to losing particular species, ecosystems or communities), that attitudes to gains and losses might not be symmetrical (losses valued more highly than gains of an equivalent magnitude), and that low-probability extreme outcomes are overweighted when making choices (Tversky and Kahneman, 1992; Quiggin, 1982). This literature suggests that under these circumstances the conventional decision axiom of choosing the policy set that maximizes the expected (monetary) value of the outcomes might not be appropriate. Non-conventional decision criteria (e.g. avoiding policy sets which imply the possibility, even if at a very low probability, of specific unacceptable outcomes) might be required to make robust decisions (Chichilnisky, 2000; Lempert and Schlesinger, 2000; Kriegler et al., 2006). No one analytic approach is optimal. Decision-making inevitably involves applying normative rules. Some normative rules are described in Section 2.2.7 and in Section 2.6. 2.2.5
Sequential decision-making
Uncertainty is a steadfast companion when analyzing the climate system, assessing future GHG emissions or the severity of climate change impacts, evaluating these impacts over many generations or estimating mitigation costs. The typology of uncertainties is explored fully in Section 2.3 below. Uncertainties of differing types exist in key socio-economic factors and scientific phenomena.
Chapter 2
Framing Issues
The climate issue is a long-term problem requiring longterm solutions. Policymakers need to find ways to explore appropriate long-term objectives and to make judgments about how compatible short-term abatement options are with long-term objectives. There is an increased focus on nonconventional (robust) decision rules (see Section 2.2.7 below), which preserve future options by avoiding unacceptable risks. Climate change decision-making is not a once-and-for-all event. Rather it is a process that will take place over decades and in many different geographic, institutional and political settings. Furthermore, it does not occur at discrete intervals but is driven by the pace of the scientific and political process. Some uncertainties will decrease with time – for example in relation to the effectiveness of mitigation actions and the availability of low-emission technologies, as well as with respect to the science itself. The likelihood that better information might improve the quality of decisions (the value of information) can support increased investment in knowledge accumulation and its application, as well as a more refined ordering of decisions through time. Learning is an integral part of the decisionmaking process. This is also referred to as ‘act then learn, then act again’ (Manne and Richels, 1992; Valverde et al., 1999). Uncertainties about climate policies at a decadal scale are a source of concern for many climate-relevant investments in the private sector (for example power generation), which have long expected economic lives. It is important to recognize, however, that some level of uncertainty is unavoidable and that at times the acquisition of knowledge can increase, not decrease, uncertainty. Decisions will nevertheless have to be made. 2.2.6
Dealing with risks and uncertainty in decision-making
Given the multi-dimensionality of risk and uncertainty discussed in Section 2.3, the governance of these deep uncertainties as suggested by Godard et al. (2002, p. 21) rests on three pillars: precaution, risk hedging, and crisis prevention and management. The 1992 UNFCCC Article 3 (Principles) states that the Parties should take precautionary measures to anticipate, prevent or minimize the causes of climate change and mitigate its adverse effects. Where there are threats of serious or irreversible damage, lack of full scientific certainty should not be used as a reason for postponing such measures, taking into account that policies and measures to deal with climate change should be cost-effective in order to ensure global benefits at the lowest possible cost.5
5
While the precautionary principle appears in many other international treaties, from a scientific perspective the concept of precaution is subject to a plurality of interpretations. To frame the discussions on precaution, three key points should be considered first. First, ‘precaution’ relates to decision-making in situations of deep uncertainty. It applies in the absence of sufficient data or conclusive or precise probabilistic descriptions of the risks (Cheve and Congar, 2000; Henry and Henry, 2002) or in circumstances where the possibility of unforeseen contingencies or the possibility of irreversibility (Gollier et al., 2000) is suspected. Second, in addition to that uncertainty/risk dimension, there is also a time dimension of precaution: the precautionary principle recognizes that policy action should not always wait for scientific certainty (see also the costs and decision-making sections of this chapter). Third, the precautionary principle cuts both ways because in many cases, as Graham and Wiener (1995) noted, environmental choices are trade-offs between one risk and another risk. For example, mitigating climate change may involve more extensive use of nuclear power. Goklany (2002) has suggested a framework for decision-making under the precautionary principle that considers trade-offs between competing risks. There is no single agreed definition of precautionary decision-making in the scientific literature. The risk of catastrophes is commercially important, particularly for reinsurers that are large companies whose business is to sell insurance to other insurance companies (see IPCC, 2007b, Chapter 7, Box 7.2). In the context of globalization and consolidation, many reinsurers are actively developing new instruments to trade some of their risk on the deeper financial markets. These instruments include options, swaps and catastrophe bonds. At the same time, governments are also developing new kinds of public-private partnership to cope with market failures, uncertainties and really big cataclysms. On a global scale, it can be argued that the best form of insurance is to increase the systemic resilience of the human society through scientific research, technical, economic and social development. This requires the broad participation of society in order to succeed. Mills (2005) concludes that the future role of insurance in helping society to cope with climate change is uncertain. Insurers may rise to the occasion and become more proactive players in improving the science and crafting responses, or they may retreat from oncoming risks, thereby shifting a greater burden to governments and individuals.
Section 2.6 discusses the ethical questions concerning burden and quantity of proof, as well as procedural issues.
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2.2.7
Decision support tools
Decisions concerning the appropriate responses to climate risks require insights into a variety of possible futures over short to very long time frames and into linkages between biophysical and human systems, as well as ethical alternatives. Structured analysis – both numerical and case-based – can ‘aid understanding by managing and analyzing information and alternatives’ (Arrow et al., 1996a, referenced in Bell et al., 2001). Integrated Assessment Models (IAMs) in particular have improved greatly in terms of the richness with which they represent the biophysical, social and economic systems and the feedbacks between them. They have increasingly explored a variety of decision rules or other means of testing alternative policies. Without structured analysis it is extremely difficult, if not impossible, to understand the possible effects of alternative policy choices that face decision-makers. Structured analysis can assist choices of preferred policies within interests (for example at the national level) as well as negotiating outcomes between interests (by making regional costs and benefits clearer). The use of projections and scenarios is one way to develop understanding about choices in the context of unpredictability. These are discussed in detail in Chapter 3. A large number of analytical approaches can be used as a support to decision-making. IPCC (2001) Chapter 10, provides an extensive overview of decision-making approaches and reviews their applicability at geopolitical levels and in climate policy domains. The review includes decision analysis, costbenefit analysis, cost-effectiveness analysis, tolerable windows/ safe-landing/guard-rail approaches, game theory, portfolio theory, public finance theory, ethical and cultural prescriptive rules, and various policy dialogue exercises. Integrated assessment, multi-attribute analysis and green accounting approaches are also commonly used decision support tools in climate change debates. A major distinction between cost benefit-analysis, costeffectiveness analysis, and multi-attribute analysis and different applications of these relates to the extent in which monetary values are used to represent the impacts considered. Cost-benefit analysis aims to assign monetary values to the full range of costs and benefits. This involves at least two important assumptions – that it is possible to ‘trade off’ or compensate between impacts on different values in a way that can be expressed in monetary values, and that it is possible to ascertain estimates of these ‘compensation’ values for non-market impacts, such as air pollution, health and biodiversity. By definition, the benefits and costs of climate change policies involve many of such issues, so climate change economic analysis embodies a lot of complicated valuation issues. Section 2.4 goes more into depth about approaches that can be used to value non-markets impacts and the question of discounting.
Chapter 2
In multi-attribute analysis, instead of using values derived from markets or from non-market valuation techniques, different dimensions (impacts) are assigned weights – through a stakeholder consultation process, by engaging a panel of experts or by the analyst making explicit decisions. This approach can use quantitative data, qualitative information or a mixture of both. Developing an overall score or ranking for each option allows alternative policies to be assessed, even under conditions of weak comparability. Different functional forms can be used for the aggregation process. Policy optimization models aim to support the selection of policy/decision strategies and can be divided into a number of types: • Cost-benefit approaches, which try to balance the costs and benefits of climate policies (including making allowances for uncertainties). • Target-based approaches, which optimize policy responses, given targets for emission or climate change impacts (again in some instances explicitly acknowledging uncertainties). • Approaches, which incorporate decision strategies (such as sequential act-learn-act decision-making, hedging strategies etc.) for dealing with uncertainty (often embedded in costbenefit frameworks). Another approach is to start with a policy or policies and evaluate the implications of their application. Policy evaluation approaches include: • Deterministic projection approaches, in which each input and output takes on a single value. • A stochastic projection approach, in which at least some inputs and outputs take on a range of value. • Exploratory modelling. • Public participation processes, such as citizens juries, consultation, and polling. IAMs aim to combine key elements of biophysical and economic systems into a decision-making framework with various levels of detail on the different sub-components and systems. These models include all different variations on the extent to use monetary values, the integration of uncertainty, and on the formulation of the policy problem with regard to optimization, policy evaluation and stochastic projections. Current integrated assessment research uses one or more of the following methods (Rotmans and Dowlatabadi, 1998): • Computer-aided IAMs to analyze the behavior of complex systems • Simulation gaming in which complex systems are represented by simpler ones with relevant behavioral similarity. • Scenarios as tools to explore a variety of possible images of the future. • Qualitative integrated assessments based on a limited, heterogeneous data set, without using any model. A difficulty with large, global models or frameworks is that it is not easy to reflect regional impacts, or equity considerations
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between regions or stakeholder groups. This is particularly true of ‘global’ cost-benefit approaches, where it is particularly difficult to estimate a marginal benefit curve, as regional differences are likely to be considerable. Such approaches have difficulty in assisting decision-making where there are many decision-makers and multiple interests and values to be taken into account. Variants of the safe landing/tolerable windows/guard rails approach emphasize the role of regional/national decisionmakers by providing them the opportunity to nominate perceived unacceptable impacts of climate change (for their region or globally), and the limit to tolerable socio-economic costs of mitigation measures they would be prepared to accept to avoid that damage (e.g. Toth 2004). Modelling efforts (in an integrated assessment model linking climate and economic variables, and with explicit assumptions about burden sharing through emissions allocations and trading) are then directed at identifying the sets of feasible mitigation paths – known as ‘emissions corridors’ – consistent with these constraints. To the extent that there is some overlap between the acceptable ‘emissions corridors’, the conditions for agreement on mitigation action do exist. Green accounting attempts to integrate a broader set of social welfare measures into macro-economic studies. These measures can be related to a broad set of social, environmental, and development-oriented policy aspects. The approach has most commonly been used in order to integrate environmental impacts, such as local air pollution, GHG emissions, waste generation, and other polluting substances, into macroeconomic studies. Green accounting approaches include both monetary valuation approaches that attempt to calculate a ‘green national product’ (where the economic values of pollutants are subtracted from the national product), and accounting systems that include quantitative non-monetary pollution data. Halsnæs and Markandya (2002) recognize that decision analysis methods exhibit a number of commonalities in assumptions. The standard approach goes through the selection of GHG emission-reduction options, selection of impact areas that are influenced by policies as for example costs, local air pollution, employment, GHG emissions, and health, definition of baseline case, assessment of the impacts of implementing the GHG emission-reduction policies under consideration, and application of a valuation framework that can be used to compare different policy impacts. Sociological analysis includes the understanding of how society operates in terms of beliefs, values, attitudes, behaviour, social norms, social structure, regarding climate change. This analysis includes both quantitative and qualitative approaches, such as general surveys, statistics analysis, focus groups, public participation processes, media content analysis, Delphi etc.
Framing Issues
All analytical approaches (explicitly or implicitly) have to consider the described elements, whether this is done in order to collect quantitative information that is used in formalized approaches or to provide qualitative information and focus for policy dialogues. Different decision-making approaches will often involve very similar technical analysis in relation to several elements. For example, multi-criteria-analysis, as well as cost-benefit analysis (as, for example, applied in integrated assessment optimization modelling frameworks) and green accounting may use similar inputs and analysis for many model components, but critically diverge when it comes to determining the valuation approach applied to the assessment of multiple policy impacts.
2.3 2.3.1
Risk and uncertainty
How are risk and uncertainty communicated in this report?
Communicating about risk and uncertainty is difficult because uncertainty is multi-dimensional and there are different practical and philosophical approaches to it. In this report, ‘risk’ is understood to mean the ‘combination of the probability of an event and its consequences’, as defined in the risk management standard ISO/IEC Guide 73 (2002). This definition allows a variety of ways of combining probabilities and consequences, one of which is expected loss, defined as the ‘product of probability and loss’. The fundamental distinction between ‘risk’ and ‘uncertainty’ is as introduced by economist Frank Knight (1921), that risk refers to cases for which the probability of outcomes can be ascertained through well-established theories with reliable complete data, while uncertainty refers to situations in which the appropriate data might be fragmentary or unavailable. Dealing effectively with the communication of risk and uncertainty is an important goal for the scientific assessment of long-term environmental policies. In IPCC assessment reports, an explicit effort is made to enhance consistency in the treatment of uncertainties through a report-wide coordination effort to harmonize the concepts and vocabulary used. The Third Assessment Report common guidelines to describe levels of confidence were elaborated by Moss and Schneider (2000). The actual application of this framework differed across the three IPCC working groups and across chapters within the groups. It led to consistent treatment of uncertainties within Working Group I (focusing on uncertainties and probabilities, see Sommerville et al., 2007, Section 1.6) and Working Group II (focusing on risks and confidence levels, see IPCC, 2007b, Section 1.1), although consistency across these groups was not achieved. The authors of Working Group III did not systematically apply the guidelines.
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Chapter 2
Box 2.1 Risk and uncertainty vocabulary used in this report Uncertainty cannot always be quantified, and thus the vocabulary displayed in Table 2.2 is used to qualitatively describe the degree of scientific understanding behind a finding or about an issue. See text for discussion of Table 2.2’s dimensions, the amount of evidence and the level of agreement. Tabel 2.2: Qualitative definition of uncertainty
Level of agreement (on a particular finding)
High agreement, limited evidence
High agreement, medium evidence
High agreement, much evidence
Medium agreement, limited evidence
Medium agreement, medium evidence
Medium agreement, much evidence
Low agreement, limited evidence
Low agreement, medium evidence
Low agreement, much evidence
Amount of evidence (number and quality of independent sources) Source: IPCC Guidance Notes on risk and uncertainty (2005).
The most important insight arising from an interdisciplinary assessment of uncertainty is its conceptual diversity. There is no linear scale going from ‘perfect knowledge’ to ‘total uncertainty’. The literature suggests a ‘pedigree’ approach for characterizing the quality of information (for example the NUSAP approach by Van der Sluijs et al., 2003). This involves examining at least the amount and reliability of evidence6 supporting the information and the level of agreement of the information sources. The degree of consensus among the available studies is a critical parameter for the quality of information. The level of agreement regarding the benefits and drawbacks of a certain technology describes the extent to which the sources of information point in the same direction. Table 2.2’s vocabulary is used to qualify IPCC findings along these two dimensions. Because mitigation mostly involves the future of technical and social systems, Table 2.2 is used here to qualify the robustness of findings, and more precise expressions regarding quantified likelihood or levels of confidence are used only when there is high agreement and much evidence, such as converging results from a number of controlled field experiments. Where findings depend on the future of a dynamic system, it is important to consider the possibility of extreme or/and irreversible outcomes, the potential for resolution (or persistence) of uncertainties in time, and the human dimensions. Rare events with extreme and/or irreversible outcomes are difficult or impossible to assess with ordinary statistics, but receive special attention in the literature. 6
2.3.2
Typologies of risk and uncertainty
The literature on risk and uncertainty offers many typologies, often comprising the following classes: Randomness: risk often refers to situations where there is a well-founded probability distribution in typologies of uncertainty. For example, assuming an unchanged climate, the potential annual supply of wind, sun or hydropower in a given area is only known statistically. In situations of randomness, expected utility maximization is a standard decision-making framework. Possibility: the degree of ‘not-implausibility’ of a future can be defined rigorously using the notion of acceptable odds, see De Finetti (1937) and Shackle (1949). While it is scientifically controversial to assign a precise probability distribution to a variable in the far distant future determined by social choices such as the global temperature in 2100, some outcomes are not as plausible as others (see the controversy on scenarios in Box 2.2). There are few possibility models related to environmental or energy economics. Knightian or Deep Uncertainty: the seminal work by Knight (1921) describes a class of situations where the list of outcomes is known, but the probabilities are imprecise. Under deep uncertainty, reporting a range of plausible values allows decision-makers to apply their own views on precaution. Two families of criteria have been proposed for decision-making in this situation. One family associates a real-valued generalized expected utility to each choice (see Ellesberg, 2001), while
“Evidence” in this report is defined as: Information or signs indicating whether a belief or proposition is true or valid. See Glossary.
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Framing Issues
the other discards the completeness axiom on the grounds that under deep uncertainty alternative choices may sometimes be incomparable (see Bewley, 2002; Walley, 1991). Results of climate policy analysis under deep uncertainty with imprecise probabilities (Kriegler, 2005; Kriegler et al. 2006) are consistent with the previous findings using classical models.
(see IPCC, 2001a, Figure SPM 2, also known as the ‘burning embers’ diagram). Fuzzy modelling has rarely been used in the climate change mitigation literature so far. Uncertainty is not only caused by missing information about the state of the world, but also by human volition: global environmental protection is the outcome of social interactions. Not mentioning taboos, psychological and social aspects, these include:
Structural uncertainty: is characterized by « unknown unknowns ». No model (or discourse) can include all variables and relationships. In energy-economics models, for example, there can easily be structural uncertainty regarding the treatment of the informal sector, market efficiency, or the choice between a Keynesian or a neoclassical view of macro-economic dynamics. Structural uncertainty is attenuated when convergent results are obtained from a variety of different models using different methods, and also when results rely more on direct observations (data) rather than on calculations.
Surprise: which means a discrepancy between a stimulus and pre-established knowledge (Kagan, 2002). Complex systems, both natural and human, exhibit behaviour that was not imagined by observers until it actually happened. By allowing decision-makers to become familiar (in advance) with a number of diverse but plausible futures, scenarios are one way of reducing surprises.
Fuzzyness or vagueness: describes the nature of things that do not fall sharply into one category or another, such as the meaning of ‘sustainable development’ or ‘mitigation costs’. One way to communicate the fuzzyness of the variables determining the ‘Reasons for concern’ about climate change is to use smooth gradients of colours, varying continuously from green to red
Metaphysical: describes things that are not assigned a truth level because it is generally agreed that they cannot be verified, such as the mysteries of faith, personal tastes or belief systems. Such issues are represented in models by critical parameters, such as discount rates or risk-aversion coefficients. While these parameters cannot be judged to be true or false they can have
Box 2.2 The controversy on quantifying the beliefs in IPCC SRES scenarios Between its Second and Third Assessment Reports, the Intergovernmental Panel on Climate Change elaborated long-term greenhouse gas emissions scenarios, in part to drive global ocean-atmosphere general circulation models, and ultimately to assess the urgency of action to prevent the risk of climatic change. Using these scenarios led the IPCC to report a range of global warming over the next century from 1.4–5.8°C, without being able to report any likelihood considerations. This range turned out to be controversial, as it dramatically revised the top-range value, which was previously 3.5°C. Yet some combinations of values that lead to high emissions, such as high per-capita income growth and high population growth, appear less likely than other combinations. The debate then fell into the ongoing controversy between the makers and the users of scenarios. Schneider (2001) and Reilly et al. (2001) argued that the absence of any probability assignment would lead to confusion, as users select arbitrary scenarios or assume equi-probability. As a remedy, Reilly et al. estimated that the 90% confidence limits were 1.1–4.5°C. Using different methods, Wigley and Raper (2001) found 1.7–4.9°C for this 1990 to 2100 warming. Grübler et al. (2002) and Allen et al. (2001) argued that good scientific arguments preclude determining objective probabilities or the likelihood that future events will occur. They explained why it was the unanimous view of the IPCC report’s lead authors that no method of assigning probabilities to a 100-year climate forecast was sufficiently widely accepted and documented to pass the review process. They underlined the difficulty of assigning reliable probabilities to social and economic trends in the latter half of the 21st century, the difficulty of obtaining consensus range for quintiles such as climate sensitivity, and the possibility of a non-linear geophysical response. Dessai and Hulme (2004) argued that scenarios could not be meaningfully assigned a probability, except relative to other specific scenarios. While a specific scenario has an infinitesimal probability given the infinity of possible futures, taken as a representative of a cluster of very similar scenarios, it can subjectively be judged more or less likely than another. Nonetheless, a set of scenarios cannot be effectively used to objectively generate a probability distribution for a parameter that is specified in each scenario. In spite of the difficulty, there is an increasing tendency to estimate probability distribution functions for climate sensitivity, discussed extensively in IPCC (2007a), see Chapter 9, Sections 9.6.2 and 9.6.3 and Chapter 10, Sections 10.5.2 and 10.5.4. 133
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a bearing on both behaviour and environmental policy-making. Thompson and Raynor (1998) argue that, rather than being obstacles to be overcome, the uneasy coexistence of different conceptions of natural vulnerability and societal fairness is a source of resilience and the key to the institutional plurality that actually enables us to apprehend and adapt to our ever-changing circumstances. Strategic uncertainty: involves the fact that information is a strategic tool for rational agents. The response to climate change requires coordination at international and national level. Strategic uncertainty is usually formalized with game theory, assuming that one party in a transaction has more (or better) information than the other. The informed party may thus be able to extract a rent from this advantage. Information asymmetry is an important issue for the regulation of firms by governments and for international agreements. Both adverse selection and moral hazards are key factors in designing efficient mechanisms to mitigate climate change. 2.3.3
Costs, benefits and uncertainties
In spite of scientific progress, there is still much uncertainty about future climate change and its mitigation costs. Given observed risk attitudes, the desirability of preventive efforts should be measured not only by the reduction in the expected (average) damages, but also by the value of the reduced risks and uncertainties that such efforts yield. The difficulty is how to value the societal benefits included in these risk reductions. Uncertainty concerning mitigation costs adds an additional level of difficulty in determining the optimal risk-prevention strategies, since the difference between two independent uncertain quantities is relatively more uncertain than related to the individual. How can we decide whether a risk is acceptable to society? Cost-benefit analysis alone cannot represent all aspects of climate change policy evaluation, and Section 2.2 on Decisionmaking discusses a variety of tools. In the private sector, another practical way to deal with these risks has been to pay attention to the Value-At-Risk (VAR): in addition to using the mean and the variance of the outcome, a norm is set on the most unfavourable percentile (usually 0.05) of the distribution of outcomes at a given future date. However, in the language of cost-benefit analysis, an acceptable risk means that its benefits to society exceed its costs. The standard rule used by public and private decisionmakers in a wide variety of fields (from road safety to long-term investments in the energy sector) is that a risk will be acceptable if the expected net present value is positive. Arrow and Lind (1970) justify this criterion when the policy’s benefits and costs have known probabilities, and when agents can diversify their own risk through insurance and other markets. For most of the economic analysis of climate change, these assumptions are disputable, and have been discussed in the economic literature. 134
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First, risks associated with climate change cannot easily be diversified using insurance and financial instruments. Atmospheric events are faced by everyone at the same time in the same region. This reduces the potential benefit of any mutual risk-sharing agreement. A solution would be to share risks internationally, but this is difficult to implement, and its efficiency depends upon the correlation of the regional damages. Inability to diversify risks, combined with the risk aversion observed in most public and private decision-makers, implies that there is an additional benefit to preventive efforts coming from the reduced variability of future damages. If these monetized damages are expressed as a percentage of GDP, the marginal benefit of prevention can be estimated as the marginal expected increase in GDP, with some adjustments for the marginal reduction in the variance of damages. Second, in most instances, objective probabilities are difficult to estimate. Furthermore, a number of climate change impacts involve health, biodiversity, and future generations, and the value of changes in these assets is difficult to capture fully in estimates of economic costs and benefits (see Section 2.4 on costs). Where we cannot measure risks and consequences precisely, we cannot simply maximize net benefits mechanically. This does not mean that we should abandon the usefulness of cost-benefit analysis, but it should be used as an input, among others in climate change policy decisions. The literature on how to account for ambiguity in the total economic value is growing, even if there is no agreed standard. Finally, Gollier (2001) suggests that a sophisticated interpretation of the Precautionary Principle is compatible with economic principles in general, and with cost-benefit analyses in particular. The timing of the decision process and the resolution of the uncertainty should be taken into account, in particular when waiting before implementing a preventive action as an option. Waiting, and thereby late reactions, yield a cost when risks happen to be worse than initially expected, but yield an option value and cost savings in cases where risks happen to be smaller than expected. Standard dynamic programming methods can be used to estimate these option values.
2.4 Cost and benefit concepts, including private and social cost perspectives and relationships to other decisionmaking frameworks 2.4.1
Definitions
Mitigation costs can be measured at project, technology, sector, and macro-economic levels, and various geographical boundaries can be applied to the costing studies (see a definition of geographical boundaries in Section 2.8).
Chapter 2
The project, technology, sector, and macro-economic levels can be defined as follows: • Project: A project-level analysis considers a ‘stand-alone’ activity that is assumed not to have significant indirect economic impacts on markets and prices (both demand and supply) beyond the activity itself. The activity can be the implementation of specific technical facilities, infrastructure, demand-side regulations, information efforts, technical standards, etc. Methodological frameworks to assess the project-level impacts include cost-benefit analysis, costeffectiveness analysis, and lifecycle analysis. • Technology: A technology-level analysis considers a specific GHG mitigation technology, usually with several applications in different projects and sectors. The literature on technologies covers their technical characteristics, especially evidence on learning curves as the technology diffuses and matures. The technology analysis can use analytical approaches that are similar to project-level analysis. • Sector: Sector-level analysis considers sectoral policies in a ‘partial-equilibrium’ context, for which other sectors and macro-economic variables are assumed to be given. The policies can include economic instruments related to prices, taxes, trade, and financing, specific large-scale investment projects, and demand-side regulation efforts. Methodological frameworks for sectoral assessments include various partial equilibrium models and technical simulation models for the energy sector, agriculture, forestry, and the transportation sector. • Macro-economic: A macro-economic analysis considers the impacts of policies across all sectors and markets. The policies include all sorts of economic policies, such as taxes, subsidies, monetary policies, specific investment programmes, and technology and innovation policies. Methodological frameworks include various macroeconomic models, such as general equilibrium models, Keynesian econometric models, and Integrated Assessment Models (IAMs), among others. In comparing project, technology, sector, and macroeconomic cost estimates it is important to bear in mind that cost estimates based on applying taxes in a macro-economic model are not comparable with abatement costs calculated at other assessment levels. This, for example, is because a carbon tax will apply to all GHG emissions, while abatement costs at project, technology or sector level will only reflect the costs of emission reductions. Private and social costs: Costs can be measured from a private as well as from a social perspective. Individual decisionmakers (including both private companies and households) are influenced by various cost elements, such as the costs of input
7
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to a production process, labour and land costs, financial interest rates, equipment costs, fuel costs, consumer prices etc., which are key private cost components. However, the activities of individuals may also cause externalities, for example emissions that influence the utility of other individuals, but which are not taken into consideration by the individuals causing them. A social cost perspective includes the value of these externalities. External costs: These typically arise when markets fail to provide a link between the person who creates the ‘externality’ and the person who is affected by it, or more generally when property rights for the relevant resources are not well defined.7 In the case of GHG emissions, those who will eventually suffer from the impacts of climate change do not have a well-defined ‘property right’ in terms of a given climate or an atmosphere with given GHG concentrations, so market forces and/or bargaining arrangements cannot work directly as a means to balance the costs and benefits of GHG emissions and climate change. However, the failure to take into account external costs, in cases like climate change, may be due not only to the lack of property rights, but also the lack of full information and nonzero transaction costs related to policy implementation. Private, financial, and social costs are estimated on the basis of different prices. The private cost component is generally based on market prices that face individuals. Thus, if a project involves an investment of US$ 5 million, as estimated by the inputs of land, materials, labour and equipment, that figure is used as the private cost. That may not be the full cost, however, as far as the estimation of social cost is concerned, because markets can be distorted by regulations and other policies as well as by limited competition that prevent prices from reflecting real resource scarcities. If, for example, the labour input is being paid more than its value in alternative employment, the private cost is higher than the social cost. Conversely, if market prices of polluting fuels do not include values that reflect the environmental costs, these prices will be lower than the social cost. Social costs should be based on market prices, but with eventual adjustments of these with shadow prices, to bring them into line with opportunity costs. In conclusion, the key cost concepts are defined as follows: • Private costs are the costs facing individual decision-makers based on actual market prices. • Social costs are the private costs plus the costs of externalities. The prices are derived from market prices, where opportunity costs are taken into account. Other cost concepts that are commonly used in the literature are ‘financial costs’ and ‘economic costs’. Financial costs, in line with private costs, are derived on the basis of market prices that face individuals. Financial costs are typically used to assess
Coase, 1960, page 2 in his essay on The Problem of Social Cost, noted that externality problems would be solved in a ‘completely satisfactory manner: when the damaging business has to pay for all damage caused and the pricing system works smoothly’ (strictly speaking, this means that the operation of a pricing system is without cost).
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the costs of financing specific investment projects. Economic costs, like social costs, assess the costs based on market prices adjusted with opportunity costs. Different from social costs, by definition they do not take all externalities into account. 2.4.2
Major cost determinants
A number of factors are critically important when determining costs, and it is important to understand their character and role when comparing mitigation costs across different studies, as occurs in Chapters 3-11 of this report, which compares costs across different models and which are based on different approaches. The critical cost factors are based on different theoretical and methodological paradigms, as well as on specific applications of approaches. This section considers a number of factors including discounting, market efficiency assumptions, the treatment of externalities, valuation issues and techniques related to climate change damages8 and other policy impacts, as well as implementation and transactions costs, and gives guidance on how to understand and assess these aspects within the context of climate change mitigation costing studies. For a more in-depth review of these issues see IPCC, 2001, Chapters 7 and 8. 2.4.2.1
value of this amount is around US$ 52,000 if a 3% discount rate is used, but only around US$ 3,000 if a discount rate of 6% is used. The prescriptive approach applies to the so-called social discount rate, which is the sum of the rate of pure time-preference and the rate of increased welfare derived from higher percapita incomes in the future. The social discount rate can thus be described by two parameters: a rate of pure preference for the present (or rate of impatience, see Loewenstein and Prelec (1992)) δ, and a factor γ that reflects the elasticity of marginal utility to changes in consumption. The socially efficient discount rate r is linked to the rate of growth of GDP per capita, g in the following formula:10
r=δ+γg Intuitively, as suggested by this formula, a larger growth in the economy should induce us to make less effort for the future. This is achieved by raising the discount rate. In an intergenerational framework, the parameter δ characterizes our ethical attitude towards future generations. Using this formula, the SAR recommended using a discount rate of 2-4%. It is fair to consider δ =0 and a growth rate of GDP per capita of 1-2% per year for developed countries and a higher rate for developing countries that anticipate larger growth rates.
Discount rates
Climate change impacts and mitigation policies have longterm characters, and cost analysis of climate change policies therefore involve a comparison of economic flows that occur at different points in time. The choice of discount rate has a very big influence on the result of any climate change cost analysis. The debate on discount rates is a long-standing one. As the SAR (Second Assessment Report) notes (IPCC, 1996, Chapter 4), there are two approaches to discounting: a prescriptive approach9 based on what rates of discount should be applied, and a descriptive approach based on what rates of discount people (savers as well as investors) actually apply in their dayto-day decisions. Investing in a project where the return is less than the standard interest rate makes the investor poorer. This descriptive approach based on a simple arbitrage argument justifies using the after-tax interest rate as the discount rate. The SAR notes that the former leads to relatively low rates of discount (around 2-3% in real terms) and the latter to relatively higher rates (at least 4% after tax and, in some cases, very much higher rates). The importance of choosing different levels of discount rates can be seen, for example when considering the value of US$ 1 million in 100 years from now. The present
8
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Portney and Weyant (1999) provide a good overview of the literature on the issue of inter-generational equity and discounting. The descriptive approach takes into consideration the market rate of return to safe investments, whereby funds can be conceptually invested in risk-free projects that earn such returns, with the proceeds being used to increase the consumption for future generations. A simple arbitrage argument to recommend the use of a real risk-free rate, such as the discount rate, is proposed. The descriptive approach relies on the assumption that credit markets are efficient, so that the equilibrium interest rate reflects both the rate of return of capital and the householders’ willingness to improve their future. The international literature includes several studies that recommend different discount rates in accordance with this principle. One of them is Dimson et al., 2000, that assesses the average real risk-free rate in developed countries to have been below 2% per year over the 20th century, and on this basis, suggests the use of a low discount rate. This rate is not incompatible with the much larger rates of return requested by shareholders on financial markets (which can be
Despite the fact that this report focuses on mitigation policies, many economic studies are structured as an integrated assessment of the costs of climate change mitigation and the benefits of avoided damages, and some of the issues related to valuation of climate change damages are therefore an integral part of mitigation studies and are briefly discussed as such in this chapter. 9 The prescriptive approach has often been termed the ‘ethical approach’ in the literature. 10 This formula is commonly known as the Ramsey rule.
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as high as 10–15%), because these rates include a premium to compensate for risk. However, the descriptive approach has several drawbacks. First, it relies on the assumption of efficient financial markets, which is not a credible assumption, both as a result of market frictions and the inability of future generations to participate in financial markets over these time horizons. Second, financial markets do not offer liquid riskless assets for time horizons exceeding 30 years, which implies that the interest rates for most maturities relevant for the climate change problem cannot be observed. Lowering the discount rate, as in the precriptive approach, increases the weight of future generations in cost-benefit analyses. However, it is not clear that it is necessarily more ethical to use a low (or lower) discount rate on the notion that it protects future generations, because that could also deprive current generations from fixing urgent problems in order to benefit future generations who are more likely to have more resources available. For discounting over very long time horizons (e.g. periods beyond 30 years), an emerging literature suggests that the discount rate should decrease over time. Different theoretical positions advocate for such an approach based on arguments concerning the uncertainty of future discount rates and economic growth, future fairness and intra-generational distribution, and on observed individual choices of discount rates (Oxera, 2002). The different theoretical arguments lead to different recommendations about the level of discount rates. Weitzman (2001) showed that if there is some uncertainty on the future return to capital, and if society is risk-neutral, the year-to-year discount rate should fall progressively to its smallest possible value. Newell and Pizer (2004) arrived at a similar conclusion. It is important to observe that this declining rate comes on top of the variable short-term discount rate, which should be frequently adapted to the conditions of the market interest rate. It is also important to link the long-term macro-economic uncertainty with the uncertainty concerning the future benefits of our current preventive investments. Obviously, it is efficient to bias our efforts towards investments that perform particularly well in the worse states (i.e., states in which the economy collapses). The standard approach to tackle this is to add a risk premium to the benefits of these investments rather than to modify the discount rate, which should remain a universal exchange rate between current and future sure consumption, for the sake of comparability and transparency of the cost-benefit analysis. Using standard financial price modelling, this risk premium is proportional to the covariance between the future benefit and the future GDP.
Framing Issues
Whereas it seems reasonable in the above formula to use a rate of growth of GDP per capita of g=1-2% for the next decade, there is much more uncertainty about which growth rate to use for longer time horizons. It is intuitive that, in the long run, the existence of an uncertain growth should reduce the discount rates for these distant time horizons. Calibrating a normative model on this idea, Gollier (2002a, 2002b, 2004) recommended using a decreasing term structure of discount rate, from 5% in the short term to 2% in the long term. In an equivalent model, but with different assumptions on the growth process, Weitzman (1998, 2004) proposed using a zero discount rate for time horizons around 50 years, with the discount rate being negative for longer time horizons. These models are in line with the important literature on the term structure of interest rates, as initiated by Vasicek (1977) and Cox, Ingersoll and Ross (1985). The main difference is the time horizon under scrutiny, with a longer horizon allowing considerable more general specifications for the stochastic process that drives the shape of the yield curve. Despite theoretical disputes about the use of time-declining discount rates, the UK government has officially recommended such rates for official approval of projects with long-term impacts. The recommendation here is to use a 3.5% rate for 1-30 years, a 3% rate for 31-75 years, a 2.5% rate for 76-125 years, a 2% rate for 125-200 years, 1.5% for 201-300 years, and 1% for longer periods (Oxera, 2002). Similarly, France decided in 2004 to replace its constant discount rate of 8% with a 4% discount rate for maturities below 30 years, and a discount rate that decreases to 2% for longer maturities.11 Finally, the US government’s Office of Management and Budget recognizes the possibility of declining rates (see appendix D of US, 2003). It is important to remember that these rates discount certainty-equivalent cash flows. This discussion does not solve the question of how to compute certainty equivalents when the project’s cash flows are uncertain. For climate change impacts, the assumed long-term nature of the problem is the key issue here. The benefits of reduced GHG emissions vary according to the time of emissions reduction, with the atmospheric GHG concentration at the reduction time, and with the total GHG concentrations more than 100 years after the emissions reduction. Because these benefits are only probabilistic, the standard costbenefit analysis can be adjusted with a transformation of the random benefit into its certainty equivalent for each maturity. In a second step, the flow of certainty-equivalent cash flows is discounted at the rates recommended above. For mitigation effects with a shorter time horizon, a country must base its decisions (at least partly) on discount rates that reflect the opportunity cost of capital. In developed countries, rates of around 4–6% are probably justified. Rates of this level
11 This should be interpreted as using a discount factor equaling (1.04)-t if the time horizon t is less than 30 years, and a discount rate equaling (1.04)-30(1.02)-(t-30) if t is more than 30 years.
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are in fact used for the appraisal of public sector projects in the European Union (EU) (Watts, 1999). In developing countries, the rate could be as high as 10–12%. The international banks use these rates, for example, in appraising investment projects in developing countries. It is more of a challenge, therefore, to argue that climate change mitigation projects should face different rates, unless the mitigation project is of very long duration. These rates do not reflect private rates of return and the discount rates that are used by many private companies, which typically need to be considerably higher to justify investments, and are potentially between 10% and 25%. 2.4.2.2
Market efficiency
The costs of climate change mitigation policies depend on the efficiency of markets, and market assumptions are important in relation to baseline cases, to policy cases, as well as in relation to the actual cost of implementing policy options. For example, the electricity market (and thereby the price of electricity that private consumers and industry face) has direct implications on the efficiency (and thereby GHG emissions) related to appliances and equipment in use. In practice, markets and public-sector activities will always exhibit a number of distortions and imperfections, such as lack of information, distorted price signals, lack of competition, and/or institutional failures related to regulation, inadequate delineation of property rights, distortion-inducing fiscal systems, and limited financial markets. Proper mitigation cost analysis should take these imperfections into consideration and assess implementation costs that include these imperfections (see Section 2.4.2.3 for a definition of implementation costs). Many project level and sectoral mitigation costing studies have identified a potential for GHG reduction options with a negative cost, implying that the benefits, including co-benefits, of implementing these options are greater than the costs. Such negative cost options are commonly referred to as ‘no-regret options’.12 The costs and benefits included in the assessment of no-regret options, in principle, are all impacts of the options including externalities. External impacts can relate to environmental sideimpacts, and distortions in markets for labour, land, energy resources, and various other areas. A presumption for the existence of no-regret options is that there are: • Market imperfections that generate efficiency losses. Reducing the existing market or institutional failures and other barriers that impede adoption of cost-effective emission reduction measures, can lower private costs compared to current practice (Larson et al., 2003; Harris
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et al., 2000; Vine et al., 2003). This can also reduce private costs overall. • Co-benefits: Climate change mitigation measures will have effects on other societal issues. For example, reducing carbon emissions will often result in the simultaneous reduction in local and regional air pollution (Dessues and O’Connor, 2003; Dudek et al., 2003; Markandya and Rubbelke, 2004; Gielen and Chen, 2001; O’Connor et al., 2003). It is likely that mitigation strategies will also affect transportation, agriculture, land-use practices and waste management and will have an impact on other issues of social concern, such as employment, and energy security. However, not all of these effects will be positive; careful policy selection and design can better ensure positive effects and minimize negative impacts. In some cases, the magnitude of cobenefits of mitigation may be comparable to the costs of the mitigating measures, adding to the no-regrets potential, although estimates are difficult to make and vary widely.13 • Double dividend: Instruments (such as taxes or auctioned permits) provide revenues to the government. If used to finance reductions in existing distortionary taxes (‘revenue recycling’), these revenues reduce the economic cost of achieving greenhouse gas reductions. The magnitude of this offset depends on the existing tax structure, type of tax cuts, labour market conditions, and method of recycling (Bay and Upmann, 2004; Chiroleu-Assouline and Fodha, 2005; Murray, et al., 2005). Under some circumstances, it is possible that the economic benefits may exceed the costs of mitigation. Contrary, it has also been argued that eventual tax distortions should be eliminated anyway, and that the benefits of reducing these therefore cannot be assigned as a benefit of GHG emission reduction policies. The existence of market imperfections, or co-benefits, and double dividends that are not integrated into markets are also key factors explaining why no-regret actions are not taken. The no-regret concept has, in practice, been used differently in costing studies, and has usually not included all the external costs and implementation costs associated with a given policy strategy.14 2.4.2.3
Transaction and implementation costs
In practice, the implementation of climate change mitigation policies requires some transaction and implementation costs. The implementation costs relate to the efforts needed to change existing rules and regulations, capacity-building efforts, information, training and education, and other institutional efforts needed to put a policy into place. Assuming that these implementation requirements are in place, there might still be costs involved in carrying through a given transaction,
12 By convention, when assessing the costs of GHG emission reductions, the benefits do not include the impacts associated with avoided climate change damages. 13 It should be recognised that, under a variety of circumstances, it may be more efficient to obtain air pollution reductions through controls targeted at such pollutants rather than coupling them with efforts to reduce GHG emissions, even if the latter results in some air pollution reductions. 14 This is due to difficulties in assessing all external costs and implementation costs, and reflects the incompleteness of the elements that have been addressed in the studies.
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for example related to legal requirements of verifying and certifying emission reduction, as in the case of CDM projects. These costs are termed ‘transaction costs’. The transaction costs can therefore be defined as the costs of undertaking a business activity or implementing a climate mitigation policy, given that appropriate implementation efforts have been (or are being) created to establish a benign market environment for this activity. Implementation policies and related costs include various elements related to market creation and broader institutional policies. In principle, mitigation studies (where possible) should include a full assessment of the cost of implementation requirements such as market reforms, information, establishment of legal systems, tax and subsidy reforms, and institutional and human capacity efforts. In practice, few studies have included a full representation of implementation costs. This is because the analytical approaches applied cannot address all relevant implementation aspects, and because the actual costs of implementing a policy can be difficult to assess ex ante. However, as part of the implementation of the emission reduction requirements of the Kyoto Protocol, many countries have gained new experiences in the effectiveness of implementation efforts, which can provide a basis for further improvements of implementation costs analysis. 2.4.2.4
Issues related to the valuation of non-market aspects
A basic problem in climate change studies is that a number of social impacts are involved that go beyond the scope of what is reflected in current market prices. These include impacts on human health, nature conservation, biodiversity, natural and historical heritage, as well as potential abrupt changes to ecosystems. Furthermore, complicated valuation issues arise in relation to both market- and non-market areas, since climate change policies involve impacts over very long time horizons, where future generations are affected, as well as intragenerational issues, where relatively wealthy and relatively poor countries face different costs and benefits of climate change impacts, adaptation and mitigation policies. Valuation of climate change policy outcomes therefore also involves assigning values to the welfare of different generations and to individuals and societies living at very different welfare levels today. The valuation of inter-generational climate change policy impacts involves issues related to comparing impacts occurring at different points in time as discussed in Section 2.4.2.1 on discount rates, as well as issues in relation to uncertainty about the preferences of future generations. Since these preferences are unknown today many studies assume, in a simplified way, that consumer preferences will stay unchanged over time. An overview of some of the literature on the preferences of future generations is given by Dasgupta et al., (1999).
Other limitations in the valuation of climate change policy impacts are related to specific practical and ethical aspects of valuing human lives and injuries. A number of techniques can be used to value impacts on human health – the costs of mortality, for example, can be measured in relation to the statistical values of life, the avoided costs of health care, or in relation to the value of human capital on the labour market. Applications of valuation techniques that involve estimating the statistical values of life will face difficulties in determining values that reflect people in a fair and meaningful way, even with very different income levels around the world. There are obviously a lot of ethical controversies involved in valuing human health impacts. In the Third Assessment Report the IPCC recognized these difficulties and recommended that studies that include monetary values of statistical values of life should use uniform average global per-capita income weights in order to treat all human beings as equal (IPCC, 2001, Chapter 7). 2.4.3
Mitigation potentials and related costs
Chapters 3-11 report the costs of climate change mitigation at global, regional, sectoral, and technology level and, in order to ensure consistency and transparency across the cost estimates reported in these chapters, it has been agreed to use a number of key concepts and definitions that are outlined in this section. Furthermore, the following paragraphs also outline how the concepts relate to mitigation cost concepts that have been used in previous IPCC reports, in order to allow different cost estimates to be compared and eventual differences to be understood. A commonly used output format for climate change mitigation cost studies means reporting the GHG emission reduction in quantitative terms that can be achieved at a given cost. The potential terminology is often used in a very ‘loose’ way, which makes it difficult to compare numbers across studies. The aim of the following is to overcome such lack of transparency in cost results based on a definition of major cost and GHG emission reduction variables to be used when estimating potentials. The term ‘potential’ is used to report the quantity of GHG mitigation compared with a baseline or reference case that can be achieved by a mitigation option with a given cost (per tonne) of carbon avoided over a given period. The measure is usually expressed as million tonnes carbon- or CO2-equivalent of avoided emissions, compared with baseline emissions. The given cost per tonne (or ‘unit cost’) is usually within a range of monetary values at a particular location (e.g. for windgenerated electricity), such as costs less than x US$ per tonne of CO2- or carbon-equivalent reduction (US$/tC-eq). The monetary values can be defined as private or social unit costs: private unit costs are based on market prices, while social unit costs reflect market prices, but also take externalities associated with the mitigation into consideration. The prices are real prices adjusted for inflation rates. 139
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2.4.3.1
Definitions of barriers, opportunities and potentials
The terms used in this assessment are those used in the Third Assessment Report (TAR). However, the precise definitions are revised and explanations for the revisions are given in the footnotes. A ‘barrier’ to mitigation potential is any obstacle to reaching a potential that can be overcome by policies and measures. (From this point onwards, ‘policies’ will be assumed to include policies, measures, programmes and portfolios of policies.) An ‘opportunity’ is the application of technologies or policies15 to reduce costs and barriers, find new potentials and increase existing ones. Potentials, barriers and opportunities all tend to be context-specific and vary across localities and over time. ‘Market potential’ indicates the amount of GHG mitigation that might be expected to occur under forecast market conditions, including policies and measures in place at the time.16 It is based on private unit costs and discount rates, as they appear in the base year and as they are expected to change in the absence of any additional policies and measures. In other words, as in the TAR, market potential is the conventional assessment of the mitigation potential at current market price, with all barriers, hidden costs, etc. in place. The baseline is usually historical emissions or model projections, assuming zero social cost of carbon and no additional mitigation policies. However, if action is taken to improve the functioning of the markets, to reduce barriers and create opportunities (e.g. policies of market transformation to raise standards of energy efficiency via labelling), then mitigation potentials will become higher. In order to bring in social costs, and to show clearly that this potential includes both market and non-market costs, ‘economic potential’ is defined as the potential for costeffective GHG mitigation when non-market social costs and benefits are included with market costs and benefits in assessing the options17 for particular levels of carbon prices in US$/ tCO2 and US$/tC-eq. (as affected by mitigation policies) and when using social discount rates instead of private ones. This includes externalities (i.e. non-market costs and benefits such as environmental co-benefits). Note that estimates of economic potential do not normally assume that the underlying structure of consumer preferences has changed. This is the proper
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theoretical definition of the economic potential, however, as used in most studies, it is the amount of GHG mitigation that is cost-effective for a given carbon price, based on social cost pricing and discount rates (including energy savings but without most externalities), and this is also the case for the studies that were reported in the TAR (IPCC, 2001, Chapters 3, 8 and 9). There is also a technical potential and a physical potential that, by definition, are not dependent on policies. The ‘technical potential’ is the amount by which it is possible to reduce greenhouse gas emissions or improve energy efficiency by implementing a technology or practice that has already been demonstrated. There is no specific reference to costs here, only to ‘practical constraints’, although in some cases implicit economic considerations are taken into account. Finally the ‘physical potential’ is the theoretical (thermodynamic) and sometimes, in practice, rather uncertain upper limit to mitigation, which also relies on the development of new technologies. A number of key assumptions are used to calculate potentials. Some of the major ones are related to: • Transformation of economic flows to net present values (NVP) or levelised costs. It is consistent here to use the financial rate of return in the discounting of private costs, and a social discount rate in social cost calculations • Treatment of GHG emission reductions that occur at different points in time. Some studies add quantitative units of GHG reductions over the lifetime of the policy, and others apply discount rates to arrive at net present values of carbon reductions. The implementation of climate change mitigation policies will involve the use of various economic instruments, information efforts, technical standards, and other policies and measures. Such policy efforts will all have impacts on consumer preferences and taste as well as on technological innovations. The policy efforts (in the short term) can be considered as an implementation cost, and can also be considered as such in the longer term, if transactions costs of policies are successfully reduced, implying that market and social- and economic potentials are increased at a given unit cost.
15 Including behaviour and lifestyle changes. 16 The TAR (IPCC, 2001), p. 352 defines market potential as ‘the amount of GHG mitigation that might be expected to occur under forecast market conditions, with no changes in policy or implementation of measures whose primary purpose is the mitigation of GHGs’. This definition might be interpreted to imply that market potential includes no implementation of GHG policies. However many European countries have already implemented mitigation policies. It is a substantial research exercise in counterfactual analysis to untangle the effects of past mitigation policies in the current levels of prices and costs and hence mitigation potential. The proposed definition simply clarifies this point. 17 IPCC (2001), Chapter 5 defines ‘economic potential’ as ‘the level of GHG mitigation that could be achieved if all technologies that are cost-effective from the consumers’ point of view were implemented’ (p. 352). This definition therefore introduces the concept of the consumer as distinct from the market. This is deeply confusing because it loses the connection with market valuations without explanation. Who is to decide how the consumers’ point of view is different from the market valuation of costs? On what basis are they to choose these costs? The definition also does not explicitly introduce the social cost of carbon and other non-market valuations necessary to account for externalities and missing markets and it is not readily comparable with the IPCC (2001), Chapter 3 definition of economic potentials. The proposed definition for this report applies to the large body of relevant literature that assesses mitigation potential at different values of the social cost of carbon, and clearly introduces non-market valuations for externalities and time preferences. The proposed definition also matches that actually used in IPCC (2001) Chapter 3, where such potentials are discussed ‘at zero social cost’ (e.g. p. 203).
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2.5 Mitigation, vulnerability and adaptation relationships 2.5.1
Integrating mitigation and adaptation in a development context – adaptive and mitigative capacities
The TAR (IPCC, 2001) introduced a new set of discussions about the institutional and developmental context of climate change mitigation and adaptation policies. One of the conclusions from that discussion was that the capacity for implementing specific mitigation and adaptation policies depends on manmade and natural capital and on institutions. Broadly speaking, institutions should be understood here as including markets and other information-sharing mechanisms, legal frameworks, as well as formal and informal networks. Subsequent work by Adger (2001a) further emphasizes the role of social capital in adaptation. Adger refers to a definition by Woolcock and Narayan (2000, p. 226), which states that social capital is made up of ‘the norms and networks that enable people to act collectively’. According to Adger there are two different views within the main areas of the international literature that are important to climate change issues namely: 1) whether social capital only exists outside the state, and 2) whether social capital is a cause, or simply a symptom, of a progressive and perhaps flexible and adaptive society. The first issue relates to how important planned adaptation and government initiatives can be, and the second considers the macro-level functioning of society and the implications for adaptive capacity. Adger observes that the role that social capital, networks and state-civil society linkages play in adaptive capacity can be observed in historical and present-day contexts by examining the institutions of resource management and collective action in climate-sensitive sectors and social groups, highlighting a number of such experiences in adaptation to climate change. The examples include an assessment of the importance of social contacts and socio-economic status in relation to excess mortality due to extreme heating, coastal defence in the UK, and coastal protection in Vietnam, where the adaptive capacity in different areas is assessed within the context of resource availability and the entitlements of individuals and groups (Kelly and Adger, 1999). A literature assessment (IPCC, 2007b, Chapter 20) includes a wider range of examples of historical studies of development patterns, thus confirming that social capital has played a key role in economic growth and stability. IPCC (2001), Chapter 1 initiated a very preliminary discussion about the concept of mitigative capacity. Mitigative capacity (in this context) is seen as a critical component of a country’s ability to respond to the mitigation challenge, and the capacity, as in the case of adaptation, largely reflects manmade and natural capital and institutions. It is concluded that development, equity and sustainability objectives, as well as
past and future development trajectories, play critical roles in determining the capacity for specific mitigation options. Following that, it can be expected that policies designed to pursue development, equity and/or sustainability objectives might be very benign framework conditions for implementing cost-effective climate change mitigation policies. The final conclusion is that, due to the inherent uncertainties involved in climate change policies, enhancing mitigative capacity can be a policy objective in itself. It is important to recognize here that the institutional aspects of the adaptive and mitigative capacities refer to a number of elements that have a ‘public-good character’ as well as general social resources. These elements will be common framework conditions for implementing a broad range of policies, including climate change and more general development issues. This means that the basis for a nation’s policy-implementing capacity exhibits many similarities across different sectors, and that capacity-enhancing efforts in this area will have many joint benefits. There may be major differences in the character of the adaptive and mitigative capacity in relation to sectoral focus and to the range of technical options and policy instruments that apply to adaptation and mitigation respectively. Furthermore, assessing the efficiency and implementability of specific policy options depends on local institutions, including markets and human and social capital, where it can be expected that some main strengths and weaknesses will be similar for different sectors of an economy. As previously mentioned, the responses to climate change depend on the adaptive and mitigative capacities and on the specific mitigation and adaptation policies adopted. Policies that enhance adaptive and mitigative capacities can include a wide range of general development policies, such as market reforms, education and training, improving governance, health services, infrastructure investments etc. The actual outcome of implementing specific mitigation and adaptation policies is influenced by the adaptive and mitigative capacity, and the outcome of adaptation and mitigation policies also depends on a number of key characteristics of the socioeconomic system, such as economic growth patterns, technology, population, governance, and environmental policies. It is expected that there may be numerous synergies and tradeoffs between the adaptive and mitigative capacity elements of the socio-economic and natural systems, as well as between specific adaptation and mitigation policies. Building more motorways, for example, can generate more traffic and more GHG emissions. However, the motorways can also improve market access, make agriculture less vulnerable to climate change, help in evacuation prior to big storms, and can support general economic growth (and thereby investments in new efficient production technologies). Similarly, increased fertiliser 141
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use in agriculture can increase productivity and reduce climate change vulnerability, but it can also influence the potential for carbon sequestration and can increase GHG emissions.
precautionary principles, including an insurance premium system, hedging strategies, and inclusion of low-probability events in risk assessments.
2.5.2
A common approach of many regional and national developing country studies on mitigation and adaptation policies has been to focus on the assessment of context-specific vulnerabilities to climate change. Given this, a number of studies and national capacity-building efforts have considered how adaptation and mitigation policies can be integrated into national development and environmental policies, and how they can be supported by financial transfers, domestic funds, and linked to foreign direct investments (IINC, 2004; CINC, 2004). The Danish Climate and Development Action Program aims at a two-leg strategy, where climate impacts, vulnerabilities, and adaptation are assessed as an integral part of development plans and actions in Danish partner countries, and where GHG emission impacts and mitigation options are considered as part of policy implementation (Danida, 2005).
Mitigation, adaptation and climate change impacts
The discussion on mitigation and adaptation policy portfolios has a global as well as a national/regional dimension. It should be recognized that mitigation and adaptation are very different regarding time frame and distribution of benefits. Dang et al. (2003, Table 1) highlights a number of important commonalities and differences between mitigation and adaptation policies. Both policy areas can be related to sustainable development goals, but differ according to the direct benefits that are global and long term for mitigation, while being local and shorter term for adaptation. Furthermore adaptation can be both reactive (to experienced climate change) and proactive, while mitigation can only be proactive in relation to benefits from avoided climate change occurring over centuries. Dang et al. (2003, Table 4) also points out that there can be conflicts between adaptation and mitigation in relation to the implementation of specific national policy options. For example, installing airconditioning systems in buildings is an adaptation option, but energy requirements can increase GHG emissions, and thus climate change. In relation to the trade-off between mitigation and adaptation, Schneider (2004) points out that when long-term integrated assessment studies are used to assess the net benefits of avoided climate change (including adaptation options) versus the costs of GHG emission reduction measures, the full range of possible climate outcomes, including impacts that remain highly uncertain such as surprises and other climate irreversibility, should be included. Without taking these uncertain events into consideration, decision-makers will tend to be more willing to accept prospective future risks rather than attempt to avoid them through abatement. It is worth noting here that,when faced with the risk of a major damage, human beings may make their judgment based on the consequences of the damage rather than on probabilities of events. Schneider concludes that it is not clear that climate surprises have a low probability, they are just very uncertain at present, and he suggests taking these uncertainties into consideration in integrated assessment models, by adjusting the climate change damage estimates. The adjustments suggested include using historical data for estimating the losses of extreme events, valuing ecosystem services, subjective probability assessments of monetary damage estimates, and the use of a discount rate that decreases over time in order to give high values to future generations. In this way the issues of jointly targeting mitigation and adaptation has an element of decision-making under uncertainty, due to the complexity of the environmental and human systems and their interactions. Kuntz-Duriseti (2004) suggests dealing with this uncertainty by combining economic analysis and 142
Burton et al. (2002) suggest that research on adaptation should focus on assessing the social and economic determinants of vulnerability in a development context. The focus of the vulnerability assessment according to this framework should be on short-term impacts, i.e. should try to assess recent and future climate variability and extremes, economic and noneconomic damages and the distribution of these. Based on this, adaptation policies should be addressed as a coping strategy against vulnerability and potential barriers, obstacles, and the role of various stakeholders and the public sector should be considered. Kelly and Adger (2000) developed an approach for assessing vulnerabilities and concluded that the vulnerability and security of any group is determined by resource availability and entitlements. The approach is applied to impacts from tropical storms in coastal areas inVietnam. On a global scale, there is a growing recognition of the significant role that developing countries play in determining the success of global climate change policies, including mitigation and adaptation policy options (Müller, 2002). Many governments of developing countries have started to realize that they should no longer discuss whether to implement any measures against climate change, but how drastic these measures should be, and how climate policies can be an integral part of national sustainable development paths (SAINC, 2003; IINC, 2004; BINC, 2004; CINC, 2004; MOST, 2004).
2.6
Distributional and equity aspects
This section discusses how different equity concepts can be applied to the evaluation of climate change policies and provides examples on how the climate literature has addressed equity issues. See also Chapter 20 in IPCC (2007b), and Chapters 12 and 13 of this report for additional discussions on the equity
Chapter 2
Framing Issues
Table 2.3: Measures of Inter-country Equity
1980/90 2001 % Change Average % Change Co. Var.
Average 3,764 7,350
GNI Per Capita US$ C.Var 4,915 10,217 95% 6%
Life Expectancy (LE) Years Average C.Var 61.2 0.18 65.1 0.21 6% 14%
Average 72.5 79.2
Literacy (ILL) % C.Var 25.3 21.4 9% -22%
Notes: Literacy rates are for 1990 and 2001. GNI and LE data are for 1980, 1990, and 2001. Ninety-nine countries are included in the sample. Coefficient of variation is the standard deviation of a series divided by the mean. The standard deviation is given by the formula:
s=
i=1
_
i
− x )2
_
(n −1)
‘
i= n
∑ (x
Where ‘x’ refers to the value of a particular observation, ‘x is the mean of the sample and ‘n’ is the number of observations.
Source: WB, 2005 (World Development Indicators)
dimensions of sustainable development and climate change policies.
remains the case, however, that actual indicators of equity still do not cover the breadth of components identified by Sen.
2.6.1
The UNDP Human Development Index (HDI) is an important attempt to widen the indicators of development, and initially included per capita national income, life expectancy at birth and the literacy rate. However, it is important to recognize that no single all-encompassing indicator can be constructed, will be understandable or useful to either policymakers or the public, so different indexes have to be used that reflect different issues and purposes.
Development opportunities and equity
Traditionally, success in development has been measured in economic terms – increase in Gross National Income (GNI) per capita remains the most common measure18. Likewise, income distribution has been one of the key components in equity, both within and between countries, and has been measured in terms of inequalities of income, through measures such as the ‘GINI’ coefficient.19 20 Although a great deal has been written in recent years on the components of well-being, the development literature has been slow to adopt a broader set of indicators of this concept, especially as far as equity in well-being is concerned, despite the fact that some authors have argued that absolute changes in income and other indicators of human wellbeing (e.g. education, mortality rates, water, sanitation etc.) are just as important as the distribution within these indicators (Maddison, 2003; Goklany, 2001). Probably the most important and forceful critic of the traditional indicators has been Sen (1992, 1999). Sen’s vision of development encompasses not only economic goods and services but also individuals’ health and life expectancy, their education and access to public goods, the economic and social security that they enjoy, and their freedom to participate freely in economic interchange and social decision-making. While his criticism is widely acknowledged as addressing important shortcomings in the traditional literature, the ideas still have not been made fully operational. Sen speaks of ‘substantive freedoms’ and ‘capabilities’ rather than goods and services as the key goals of development and provides compelling examples of how his concepts can paint a different picture of progress in development compared to that of changes in GNI. It
Rather than synthesizing these three components into a single index, as the HDI has done, we can also look at changes in the inter-country equity of the individual components. Table 2.321 provides data for the period 1980–2001 for per capita national income (GNI) and life expectancy at birth (LE) and from 1990 to 2001 for the literacy rate (ILL). The increase in average GNI has been much faster over this period than those of life expectancy and literacy rates. The increase in coefficient of variations for GNI per capita (by 6%) and life expectancy (by 14%) therefore show an increase in dispersion over this period, indicating a wider disparity of these parameters across countries. However, literacy rates have become more equal, with a decline in the coefficient of variation by 22% (see Table 2.3). However, a study by Goklany (2002) concluded that inequality between countries does not necessarily translate into inequality between individuals. As Sen notes, the problem of inequality becomes magnified when attention is shifted from income inequality to inequality of ‘substantive freedoms and capabilities’, as a result of a ‘coupling’ of the different dimensions – individuals who are likely to suffer from higher mortality and who are illiterate are also likely to have lower incomes and a lower ability to convert
18 The Gross National Income measures the income of all citizens, including income from abroad. GDP is different to GNI as it excludes income from abroad. 19 The GINI coefficient is a measurement standard for the total income that needs to be redistributed if all income was equally distributed. A 0 value means that all are equal, while a 1 value implies considerable inequality. 20 When income distribution is used in equity assessments it is important to recognize that such measures do not include all aspects of justice and equity. 21 Ideally one should use purchasing power (PPP) adjusted GNI, but data on GNIppp is much more limited for the earlier period. For LE and ILL we also looked at a larger dataset of 142 countries, and found very similar results.
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incomes into capabilities and good standards of living. While this is certainly true at the individual level, at the country level the correlation appears to be declining. This wider analysis of equity has important implications for sharing the costs of mitigation and for assessing the impacts of climate change (see Chapter 1 for a more detailed discussion of climate change impacts and the reference to the UNFCCC Article 2). As generally known, the impacts of climate change are distributed very unequally across the planet, hurting the vulnerable and poor countries of the tropics much more than the richer countries in the temperate regions. Moreover, these impacts do not work exclusively, or even mainly, through changes in real incomes. The well-being of future generations will be affected through the effects of climate change on health, economic insecurity and other factors. As far as the costs of actions to reduce GHGs are concerned, measures that may be the least costly in overall terms are often not the ones that are the most equitable – see Sections 2.6.4 and 2.6.5 for a further discussion of the links between mitigation policy and equity. 2.6.2
Uncertainty as a frame for distributional and equity aspects
Gollier, 2001 outlines a framework for assessing the equity implications of climate change uncertainty, where he considers risk aversion for different income groups. The proposition (generally supported by empirical evidence) is that the relative risk aversion of individuals decreases with increasing wealth (Gollier, 2001), implying that the compensation that an individual asks for in order to accept a risk decreases relative to his income with increasing income. However, the absolute risk aversion – or the total compensation required in order to accept a risk – increases with wealth. It means that a given absolute risk level is considered to be more important to poorer people than to richer, and the comparatively higher risk aversion of poorer people suggests that larger investments in climate change mitigation and adaptation policies are preferred if these risks are borne by the poor rather than the rich. A similar argument can be applied in relation to the equity consequences of increased climate variability and extreme events. Climate change may increase the possibility of large, abrupt and unwelcome regional or global climatic events. A coping strategy against variability and extreme events can be income-smoothing measures, where individuals even out their income over time through savings and investments. Poorer people with a lower propensity to save, and with less access to credit makers, have smaller possibilities to cope with climate variability and extreme events through such income-smoothing measures, and they will therefore be more vulnerable.
Chapter 2
2.6.3
Alternative approaches to social justice
Widening our understanding of equity does not provide us with a rule for ranking different outcomes, except to say that, other things being equal, a less inequitable outcome is preferable to a more inequitable one. But how should one measure outcomes in terms of equity and what do we do when other things are not equal? The traditional economic approach to resource allocation has been based on utilitarianism, in which a policy is considered to be desirable if no other policy or action is feasible that yields a higher aggregate utility for society. This requires three underlying assumptions: (a) All choices are judged in terms of their consequences, and not in terms of the actions they entail. (b) These choices are valued in terms of the utility they generate to individuals and no attention is paid to the implications of the choices for aspects such as rights, duties etc. (c) The individual utilities are added up to give the sum of utility for society as a whole. In this way the social welfare evaluation relies on the assumption that there is a net social surplus if the winners can compensate the losers and still be better off themselves. It should be recognized here that philosophers dispute that efficiency is a form of equity. This approach has been the backbone of welfare economics, including the use of cost-benefit analysis (CBA) as a tool for selecting between options. Under CBA all benefits are added up, as are the costs, and the net benefit – the difference between the benefits and costs – is calculated. The option with the highest net benefit is considered the most desirable.22 If utilities were proportional to money benefits and ‘disutilities’ were proportional to money costs, this method would amount to choosing to maximize utilities. Since most economists accept that this proportionality does not hold, they extend the CBA by either (a) asking the decision-maker to take account of the distributional implications of the option as a separate factor, in addition to the calculated net benefit; or (b) weighting costs or benefits by a factor that reflects the relationship between utility and the income of the person receiving that cost or benefit. For details of these methods in the context of climate change, see Markandya and Halsnaes (2002b).23 An alternative approach to allocating resources, which is derived from an ethical perspective and has existed for at least as long as the utilitarian approach described above (which has its modern origins in the late 18th century by Jeremy Bentham), is based on the view that social actions are to be judged by whether or not they conform to a ‘social contract’ that defines the rights and duties of individuals in society. The view was
22 This is considerably simplified; ignoring the time dimension and market imperfections in valuing costs and benefits but the principle remains valid. 23 The ability of CBA to combine equity and utility through these means has been challenged by philosophers who argue that there could be serious ethical problems with combining the two when benefits and costs are as hugely disaggregated, as is the case with climate change. See Brown, 2002.
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inspired by the work of Kant and Hegel and finds its greater articulation in the writing of Rousseau and the French 19th century philosophers.24 In this position, for example, a society may predetermine that an individual has the right to be protected from serious negative health damage as a result of social actions. Hence no action, even if it increased utility, could be tolerated if it violated the rights and duties of individuals. Modern philosophers who have developed the ‘rights’ view include Rawls, who argued that it is not utilities that matter but the distribution of ‘primary goods, which include, in addition to income, “rights, liberties and opportunities and… the social basis of self respect”’ (Rawls, 1971). Rawls argued further that social justice demanded that society be judged in terms of the level of well-being of its worst-off member. At the other end of the political spectrum, Nozick and the modern libertarians contend that personal liberties and property rights have (with very few exceptions) absolute precedence over objectives such as the reduction of poverty and deprivation (Nozick, 1974). More recently, however, some ethical philosophers have found fault with both the ‘modified’ utilitarian view and the rights-based approach, on a number of grounds. Sen, for example, has argued that options should be judged not only in terms of their consequences, but also in terms of procedures. He advocates a focus on the capabilities of individuals to choose a life that one has reason to value. A person’s capability refers to the alternative combinations of ‘functionings’, where functionings can be more popularly described as ‘lifestyles’ (Sen, 1999, pp. 74-75). What matters are not only the realized functionings, but also the capability set of alternatives, differently from a utilitarian-based approach that focuses only on the outcomes. In particular, the freedom to make the choices and engage in social and market transactions is worth something in its own right. Sen criticizes the ‘rights-based’ equity approaches for not taking into consideration the fact that individuals are different and the actual consequences of giving them specific rights will vary between individuals, so rights should be seen in the context of capabilities. Both apply, because individuals have different preferences and thereby value primary inputs, for example, differently, and because their capability to use different rights also differ. Along these lines, Sen further argues that his capability-based approach can facilitate easier inter-personal comparisons than utilitarianism, since it does not suggest aggregating all individuals, but rather presenting information both on the capability sets available to individuals and their actual achievements. What implications does this debate have in the context of climate change? One is that rights and capabilities need to be viewed in an international context. An example of an approach based on global equity would be to entitle every individual alive
Framing Issues
at a given date an equal per capita share in the intrinsic capacity of the earth to absorb GHGs. Countries whose total emissions exceeded this aggregate value would then compensate those below the value. In accordance with a utilitarian approach this compensation would be based on an estimate of the aggregate economic welfare lost by countries due to climate change, seen in relation to their own emissions. In contrast, the capabilitybased approach would argue for reduced capabilities associated with climate change. As suggested above, societies do not (in practice) follow a strict utilitarian view of social justice and they do indeed recognize that citizens have certain basic rights in terms of housing, medical care etc. Equally, they do not subscribe to a clear ‘rights’ view of social justice either. Social choices are then a compromise between a utilitarian solution that focuses on consequences and one that recognizes basic rights in a more fundamental way. Much of the political and philosophical debate is about which rights are valid in this context – a debate that shows little sign of resolution. For climate change there are many options that need to be evaluated, in terms of their consequences for the lives of individuals who will be impacted by them. It is perfectly reasonable for the policymakers to exclude those that would result in major social disruptions, or large number of deaths, without recourse to a CBA. Equally, choices that avoid such negative consequences can be regarded as essential, even if the case for them cannot be made on CBA grounds. Details of where such rules should apply and where choices can be left to the more conventional CBA have yet to be worked out, and this remains an urgent part of the agenda for climate change studies. As an alternative to social-justice-based equity methods, eco-centric approaches assign intrinsic value to nature as such (Botzler and Armstrong, 1998). This value can be specified in terms of diversity, avoided damages, harmony, stability, and beauty, and these values should be respected by human beings in their interaction with nature. In relation to climate change policies the issue here becomes one of specifying the value of nature such that it can be addressed as specific constraints that are to be respected beyond what is reflected in estimates of costs and benefits and other social impacts. 2.6.4
Equity consequences of different policy instruments
All sorts of climate change policies related to vulnerabilities, adaptation, and mitigation will have impacts on intra- and intergenerational equity. These equity impacts apply at the global, international, regional, national and sub-national levels. Article 3 of the UNFCCC (1992, sometimes referred to as ‘the equity article’) states that Parties should protect the
24 For a discussion of this debate in an economic context, see Phelps, 1973.
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climate system on the basis of equity and in accordance with their common but differentiated responsibilities and respective capabilities. Accordingly, the developed country Parties should take the lead in combating climate change and the adverse effects thereof. Numerous approaches exist in the climate change discourse on how these principles can be implemented. Some of these have been presented to policymakers (both formally and informally) and have been subject to rigorous analysis by academics, civil society and policymakers over long periods of time. The equity debate has major implications for how different stakeholders judge different instruments for reducing greenhouse gases (GHG) and for adapting to the inevitable impacts of climate change. With respect to the measures for reducing GHGs, the central equity question has focused on how the burden should be shared across countries (Markandya and Halsnaes, 2002b; Agarwal and Narain, 1991; Baer and Templet, 2001; Shukla, 2005). On a utilitarian basis, assuming declining marginal utility, the case for the richer countries undertaking more of the burden is strong – they are the ones to whom the opportunity cost of such actions would have less welfare implications. However, assuming constant marginal utility, one could come to the conclusion that the costs of climate change mitigation that richer countries will face are very large compared with the benefits of the avoided climate change damages in poorer countries. In this way, utilitarian-based approaches can lead to different conclusions, depending on how welfare losses experienced by poorer people are represented in the social welfare function. Using a ‘rights’ basis it would be difficult to make the case for the poorer countries to bear a significant share of the burden of climate change mitigation costs. Formal property rights for GHG emissions allowances are not defined, but based on justice arguments equal allocation to all human beings has been proposed. This would give more emissions rights to developing countries – more than the level of GHGs they currently emit. Hence such a rights-based allocation would impose more significant costs on the industrialized countries, although now, as emissions in the developing world increased, they too, at some point in time, would have to undertake some emissions reductions. The literature includes a number of comparative studies on equity outcomes of different international climate change agreements. Some of these studies consider equity in terms of the consequences of different climate change policies, while others address equity in relation to rights that nations or individuals should enjoy in relation to GHG emission and the global atmosphere.
Chapter 2
Equity concerns have also been addressed in a more pragmatic way as a necessary element in international agreements in order to facilitate consensus. Müller (2001) discusses fairness of emission allocations and that of the burden distribution that takes all climate impacts and reduction costs into consideration and concludes that there is no solution that can be considered as the right and fair one far out in the future. The issue is rather to agree on an acceptable ‘fairness harmonization procedure’, where an emission allocation is initially chosen and compensation payments are negotiated once the costs and benefits actually occur. Rose et al. (1998) provide reasons why equity considerations are particularly important in relation to climate change agreements. First, country contributions will depend on voluntary compliance and it must therefore be expected that countries will react according to what they consider to be fair,25 which will be influenced by their understanding of equity. Second, appealing to global economic efficiency is not enough to get countries together, due to the large disparities in current welfare and in welfare changes implied by efficient climate policies. Studies that focus on the net costs of climate change mitigation versus the benefits of avoided climate change give a major emphasis to the economic consequences of the policies, while libertarian-oriented equity studies focus on emission rights, rights of the global atmosphere, basic human living conditions etc. (Wesley and Peterson, 1999). Studies that focus on the net policy costs will tend to address equity in terms of a total outcome of policies, while the libertarian studies focus more on initial equity conditions that should be applied to ex ante emission allocation rules, without explicitly taken equity consequences into consideration. Given the uncertainties inherent in climate change impacts and their economic and social implications, it is difficult to conduct comprehensive and reliable consequence studies that can be used for an ex ante determination of equity principles for climate change agreements. Furthermore, social welfare functions and other value functions, when applied to the assessment of the costs and benefits of global climate change policies, run into a number of crucial equity questions. These include issues that are related to the asymmetry between the concentration of major GHG emission sources in industrialized countries and the relatively large expected damages in developing countries, the treatment of individuals with different income levels in the social welfare function, and a number of inter-generational issues. Rights-based approaches have been extensively used as a basis for suggestions on structuring international climate change
25 What countries consider as ‘fair’ may be in conflict with their narrow self-interest. Hence there is a problem with resolving the influence of these two determinants of national contributions to reducing GHGs. One pragmatic element in the resolution could be that the difference between the long-term self interest and what is fair is much smaller than that between narrow self-interest and fairness.
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agreements around emission allocation rules or compensation mechanisms. Various allocation rules have been examined, including emissions per capita principles, emissions per GDP, grandfathering, liability-based compensation for climate change damages etc. These different allocation rules have been supported with different arguments and with reference to equity principles. An overview and assessment of the various rights-based equity principles and their consequences on emission allocations and costs are included in Rose et al. (1998), Valliancourt and Waaub (2004), Leimbach (2003), Tol and Verheyen (2004) and Panayotou et al. (2002). While there is consensus in the literature about how rules should be assessed in relation to specific moral criteria, there is much less agreement on what criteria should apply (e.g. should they be based on libertarian or egalitarian rights-based approaches, or on utilitarian approaches). A particular difficulty in establishing international agreements on emission allocation rules is that the application of equity in this ex ante way can imply the very large transfer of wealth across nations or other legal entities that are assigned emission quotas, at a time where abatement costs, as well as climate change impacts, are relatively uncertain (Halsnæs and Olhoff, 2005). These uncertainties make it difficult for different parties to assess the consequences of accepting given emission allocation rules and to balance emission allocations against climate damages suffered in different parts of the world (Panayotou et al., 2002). Practical discussions about equity questions in international climate change negotiations have reflected, to a large extent, specific interests of various stakeholders, more than principal moral questions or considerations about the vulnerability of poorer countries. Arguments concerning property rights, for example, have been used by energy-intensive industries to advocate emission allocations based on grandfathering principles that will give high permits to their own stakeholders (that are large past emitters), and population-rich countries have, in some cases, advocated that fair emission allocation rules imply equal per capita emissions, which will give them high emission quotas. Vaillancourt and Waaub (2004) suggest designing emission allocation criteria on the basis of the involvement of different decision-makers in selecting and weighing equity principles for emission allocations, and using these as inputs to a multi-criteria approach. The criteria include population basis, basic needs, polluter pays, GDP intensity, efficiency and geographical issues, without a specified structure on inter-relationships between the different areas. In this way, the approach primarily facilitates the involvement of stakeholders in discussions about equity.
Framing Issues
2.6.5
Economic efficiency and eventual trade-offs with equity
For more than a decade the literature has covered studies that review the economic efficiency of climate change mitigation policies and, to some extent, also discuss different emission allocation rules and the derived equity consequences (IPCC, 1996, Chapter 11; IPCC, 2001, Chapters 6 and 8). Given that markets for GHG emission permits work well in terms of competition, transparency and low transaction costs, trade-offs between economic efficiency and equity (resulting from the distribution of emission rights) do not need to occur. In this ideal case, equity and economic efficiency can be addressed separately, where equity is taken care of in the design of emission allocation rules, and economic efficiency is promoted by the market system. In practice, however, emission markets do not live up to these ideal conditions and the allocation of emission permits, both in international and domestic settings, will have an influence on the structure and functioning of emission markets, so trade-offs between what seems to be equitable emission allocations and economic efficiency can often occur (Shukla, 2005). Some of the issues that have been raised in relation to the facilitation of equity concerns through initial emission permit allocations include the large differences in emission permits and related market power that different countries would have (Halsnæs and Olhoff, 2005).
2.7
Technology
The cost and pace of any response to climate change concerns will also depend critically on the cost, performance, and availability of technologies that can lower emissions in the future. These technologies include both end-use (demand) as well as production (supply) technologies. Technological change is particularly important over the long time scales characteristic of climate change. Decade or century-long time scales are typical for the lags involved between technological innovation and widespread diffusion and of the capital turnover rates characteristic for long-lived energy capital stock and infrastructures (IPCC, 2001, 2002). The development and deployment of technology is a dynamic process involving feedbacks. Each phase of this process may involve a different set of actors and institutions. The state of technology and technology change can differ significantly from country to country and sector to sector, depending on the starting point of infrastructure, technical capacity, the readiness of markets to provide commercial opportunities and policy frameworks. This section considers foundational issues related to the creation and deployment of new technology.
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‘Technology’ refers to more than simply devices. Technology includes hardware (machines, devices, infrastructure networks etc.), software (i.e. knowledge/routines required for the production and use of technological hardware), as well as organizational/institutional settings that frame incentives and deployment structures (such as standards) for the generation and use of technology (for a review, compare Grubler, 1998).26 Both the development of hybrid car engines and the development of Internet retailing mechanisms represent technological changes. Many frameworks have been developed to simplify the process of technological change into a set of discrete phases. A common definitional framework frequently includes the following phases: (1) Invention (novel concept or idea, as a result of research, development, and demonstration efforts). (2) Innovation (first market introduction of these ideas). (3) Niche markets (initial, small-scale applications that are economically feasible under specific conditions). (4) Diffusion (widespread adoption and the evolution into mature markets, ending eventually in decline) (see Figure 2.3 below). While the importance of technology to climate change is widely understood, there are differing viewpoints on the feasibility of current technology to address climate change and the role of new technology. On the one hand, Hoffert et al. (2002) and others have called for a major increase in research funding now to develop innovative technological options because, in this view, existing technologies cannot achieve the deep emission cuts that could be needed to mitigate future change. On the other hand, Pacala and Socolow (2004) advance the view that a range of known current technologies could be deployed, starting now and over the next 50 years, to place society on track to stabilize CO2 concentrations at 500 ± 50 parts per million. In their view, research for innovative technology is needed but only to develop technologies that might be used in the second half of the century and beyond. Still a third viewpoint is that the matter is better cast in terms of cost, in addition to technical feasibility (e.g. Edmonds et al., 1997; Edmonds, 2004; Nakicenovic and Riahi, 2002) From this viewpoint, today’s technology is, indeed, sufficient to bring about the requisite emissions reductions, but the underlying question is not technical feasibility but the degree to which resources would need to be reallocated from other societal goals (e.g. health care, education) to accommodate emissions mitigation. The role of new technology, in this view, is to lower the costs to achieve societal goals. From the perspective of (commercial) availability and costs it is important to differentiate between the short-term and the long-term, and between technical and economic feasibility. A
Chapter 2
technology, currently at a pilot plant development stage and thus not available commercially, has no short-term potential to reduce emissions, but might have considerable potential once commercialized. Conversely, a technology, currently available commercially, but only at high cost, might have a short-term emission reduction potential in the (unlikely) case of extremely strong short-term policy signals (e.g. high carbon prices), but might have considerable potential in the long-term if the costs of the technology can be reduced. Corresponding mitigation technology assessments are therefore most useful when they differentiate between short/medium-term and longterm technology options, (commercial) availability status, costs, and the resulting (different) mitigation potentials of individual technology options. Frequently, the resulting ranking of individual technological options with respect to emissions reduction potentials and costs/yields emission abatement ‘supply curves’ illustrate how much emission reductions can be achieved, at what costs, over the short- to medium-term as well as in the longer-term. 2.7.1
Technology and climate change
Recognizing the importance of technology over the longterm introduces an important element of uncertainty into the climate change debate, as direction and pace of future technological change cannot be predicted. Technological innovation and deployment are responsive to climate policy signals, for example in form of carbon taxes, although the extent and rate of this response can be as uncertain as the timing and magnitude of the policy signal. Reducing such uncertainties, for instance through long-term, predictable policy frameworks and signals, are therefore important. The usual approach consists of formulating alternative scenarios of plausible future developments. These, however, are constrained by inherent biases in technology assessment and uncertainties concerning the response of technological change to climate policy. There is also widespread recognition in the literature that it is highly unlikely that a single ‘silver bullet’ technology exists that can solve the climate problem, so the issue is not one of identifying singular technologies, but rather ensembles, or portfolios of technologies. This applies to both mitigation and adaptation technologies. These technologies have inter-dependencies and cross-enhancement (‘spillover’) potentials, which adds another important element of uncertainty into the analysis. Despite these problems of uncertainty and ignorance, insights are available from multiple fields. Extensive literature surveys on the importance of technological change on the extent of possible climate change and on feasibility and costs of climate policies are provided by Clarke and Weyant (2002), Grubb et al. (2002), Grübler et al. (1999), Jaffe et al. (2003) and Löschel (2002) among others.
26 It is also important to note that important linkages exist between technological and behavioural change. A frequently discussed phenomenon is so-called ‘take-back’ or ‘rebound’ effects, e.g. a change in consumption behaviour after the adoption of energy efficiency improvement measures (e.g. driving longer distances after purchasing a more energy-efficient car). Compare the review by Schipper and Grubb, 2000.
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Framing Issues
Quantitative illustrations have been published in a number of important scenario studies including the IPCC SAR (IPCC, 1996) and SRES (IPCC, 2000), the scenarios of the World Energy Council (WEC, Nakicenovic et al., 1998a) as well as from climate policy model inter-comparison projects such as EMF-19 (Energy Modelling Forum) (Weyant, 2004b), the EU-based Innovation Modeling Comparison Project (IMCP) (Edenhofer et al., 2006) and the multi-model calculations of climate ‘stabilization’ scenarios summarized in the TAR (IPCC, 2001). In a new development since the TAR, technology has also moved to the forefront of a number of international and national climate policy initiatives, including the Global Energy Technology Strategy (GTSP, 2001), the Japanese ‘New Earth 21’ Project (RITE, 2003), the US 21 Technology Roadmap (NETL, 2004), or the European Union’s World Energy Technology Outlook (WETO, 2003). The subsequent review first discusses the importance of technological change in ‘no-climate policy’ (or so-called ‘reference’ or ‘baseline’) scenarios, and hence the magnitude of possible climate change. The review then considers the role of alternative technology assumptions in climate policy (‘stabilization’) scenarios. The review continues by presenting a discussion of the multitude of mechanisms underlying technological change that need to be considered when discussing policy options to further the availability and economics of mitigation and adaptation technologies. 2.7.1.1
Technological change in no-climate policy (reference) scenarios
The importance of technological change for future GHG emission levels and hence the magnitude of possible climate change has been recognized ever since the earliest literature reviews (Ausubel and Nordhaus, 1983). Subsequent important literature assessments (e.g. Alcamo et al., 1995; Nakicenovic et al., 1998b; Edmonds et al., 1997; SRES, 2000) have examined the impact of alternative technology assumptions on future levels of GHG emissions. For instance, the SRES (2000) report concluded technology to be of similar importance for future GHG emissions as population and economic growth combined. A conceptual simple illustration of the importance of technology is provided by comparing individual GHG emission scenarios that share comparable assumptions on population and economic growth, such as in the Low Emitting Energy Supply Systems (LESS) scenarios developed for the IPCC SAR (1996) or within the IPCC SRES (2000) A1 scenario family, where for a comparable level of energy service demand, the (no-climatepolicy) scenarios span a range of between 1038 (A1T) and 2128 (A1FI) GtC cumulative (1990-2100) emissions, reflecting different assumptions on availability and development of low- versus high-emission technologies. Yet another way of illustrating the importance of technology assumptions in baseline scenarios is to compare given scenarios with a hypothetical baseline in which no technological change is assumed to occur at all. For instance, GTSP (2001) and Edmonds et al. (1997, see
also Figure 3.32 in Chapter 3) illustrate the effect of changing reference case technology assumptions on CO2 emissions and concentrations based on the IPCC IS92a scenario by holding technology at 1990 levels to reveal the degree to which advances in technology are already embedded in the non-climate-policy reference case, a conclusion also confirmed by Gerlagh and Zwaan, 2004. As in the other scenario studies reviewed, the degree to which technological change assumptions are reflected in the scenario baseline by far dominates future projected emission levels. The importance of technology is further magnified when climate policies are considered. See for example, the stabilization scenarios reviewed in IPCC TAR (2001) and also Figure 2.1 below. Perhaps the most exhaustive examination of the influence of technological uncertainty to date is the modelling study reported by Gritsevskyi and Nakicenovic (2000). Their model simulations, consisting of 130,000 scenarios that span a carbon emission range of 6 to 33 GtC by 2100 (Figure 2.1), provided a systematic exploration of contingent uncertainties of longterm technological change spanning a comparable range of future emissions as almost the entirety of the no-climate policy emissions scenario literature (see Chapter 3 for an update of the scenario literature). The study also identified some 13,000 scenarios (out of an entire scenario ensemble of 130,000) regrouped into a set of 53 technology dynamics that are all ‘optimal’ in the sense that they satisfy the same cost minimum in the objective function, but with a bimodal distribution in terms of emissions outcomes. In other words, considering full endogenous technological uncertainty produces a pattern of ‘technological lock-in’ into alternatively low or high emissions futures that are equal in terms of their energy systems costs.
5.5
Relative frequency (%) Set of 520 technology dynamics
5.0 4.5 4.0 3.5 3.0 2.5 2.0
Optimal set of 53 technology dynamics
1.5 1.0 0.5 0.0 5
10
15
20
25
30
GtC Figure 2.1: Emission impacts of exploring the full spectrum of technological uncertainty in a given scenario without climate policies. Relative frequency (percent) of 130,000 scenarios of full technological uncertainty regrouped into 520 sets of technology dynamics with their corresponding carbon emissions by 2100. Also shown is a subset of 13,000 scenarios grouped into 53 sets of technology dynamics that are all ‘optimal’ in the sense of satisfying a cost minimization criterion in the objective function. See text for further discussion. 1 Gt C = 3.7 Gt CO2 Source: Adapted from Gritsevskyi and Nakicenovic, 2000.
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This finding is consistent with the extensive literature on technological ‘path dependency’ and ‘lock-in phenomena’ (e.g. Arthur, 1989) as also increasingly reflected in the scenario literature (e.g. Nakicenovic et al., 1998b and the literature review in Chapter 3). This casts doubts on the plausibility of central tendency technology and emissions scenarios. It also shows that the variation in baseline cases could generate a distribution of minimum costs of the global energy system where low-emission baseline scenarios could be as cheap as their high-emission counterparts. The results also illustrate the value of technology policy as a hedging strategy aiming at lowering future carbon emissions, even in the absence of directed climate policies, as the costs of reducing emissions even further from a given baseline are ceteris paribus proportionally lower with lower baseline emissions. 2.7.1.2
Technological change in climate policy scenarios
In addition to the technology assumptions that enter typical ‘no-climate policy’ baselines, technology availability and the response of technology development and adoption rates to a variety of climate policies also play a critical role. The assessment of which alternative technologies are deployed in meeting given GHG emission limitations or as a function of ex ante assumed climate policy variables, such as carbon taxes, again entails calculations that span many decades into the future and typically rely on (no-climate policy) baseline scenarios (discussed above). Previous IPCC assessments have discussed in detail the differences that have arisen with respect to feasibility and costs of emission reductions between two broad categories of modelling approaches: ‘bottom-up’ engineering-type models versus ‘top-down’ macro-economic models. Bottom-up models usually tend to suggest that mitigation can yield financial and economic benefits, depending on the adoption of best-available technologies and the development of new technologies. Conversely, top-down studies have tended to suggest that mitigation policies have economic costs because markets are assumed to have adopted all efficient options already. The TAR offered an extensive analysis of the relationship between technological, socio-economic, economic and market potential of emission reductions, with some discussion of the various barriers that help to explain the differences between the different modeling approaches. A new finding in the underlying literature (see, for example, the review in Weyant, 2004a) is that the traditional distinction between ‘bottom-up’ (engineering) and ‘top down’ (macro-economic) models is becoming increasingly blurred as ‘top down’ models incorporate increasing technology detail, while ‘bottom up’ models increasingly
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incorporate price effects and macro-economic feedbacks, as well as adoption barrier analysis, into their model structures. The knowledge gained through successive rounds of model inter-comparisons, such as implemented within the Energy Modeling Forum (EMF) and similar exercises, has shown that the traditional dichotomy between ‘optimistic’ (i.e. bottom-up) and ‘pessimistic’ (i.e. top-down) views on feasibility and costs of meeting alternative stabilization targets is therefore less an issue of methodology, but rather the consequence of alternative assumptions on availability and costs of low- and zero-GHGemitting technologies. However, in their meta-analysis of postSRES model results, Barker et al. (2002) have also shown that model structure continues to be of importance. Given the infancy of empirical studies and resulting models that capture in detail the various inter-related inducement mechanisms of technological change in policy models, salient uncertainties continue to be best described through explorative model exercises under a range of (exogenous) technology development scenarios. Which mitigative technologies are deployed, how much, when and where depend on three sets of model and scenario assumptions. First, assumptions on which technologies are used in the reference (‘no policy’) case, in itself a complex result of scenario assumptions concerning future demand growth, resource availability, and exogenous technology-specific scenario assumptions. Second, technology deployment portfolios depend on the magnitude of the emission constraint, increasing with lower stabilization targets. Finally, results depend critically on assumptions concerning future availability and relative costs of mitigative technologies that determine the optimal technology mix for any given combination of baseline scenarios with alternative stabilization levels or climate policy variables considered. 2.7.1.3
Technological change and the costs of achieving climate targets
Rates of technological change are also critical determinants of the costs of achieving particular environmental targets. It is widely acknowledged that technological change has been a critical factor in both cost reductions and quality improvements of a wide variety of processes and products.27 Assuming that technologies in the future improve similarly to that observed in the past enables experts to quantify the cost impacts of technology improvements in controlled modeling experiments. For instance, Edmonds et al. (1997, compare Figure 3.36 in Chapter 3) analyzed the carbon implications of technological progress consistent with historical rates of energy technology change. Other studies have confirmed Edmonds’ (1997) conclusion on the paramount importance of future availability and costs of low-emission technologies and the significant economic benefits of improved technology
27 Perhaps one of the most dramatic historical empirical studies is provided by Nordhaus (1997) who has analyzed the case of illumination since antiquity, illustrating that the costs per lumen-hour have decreased by approximately a factor of 1,000 over the last 200 years. Empirical studies into computers and semiconductors indicate cost declines of up to a factor of 100,000 (Victor and Ausubel, 2002; Irwin and Klenov, 1994). Comparable studies for environmental technologies are scarce.
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that, when compounded over many decades, can add up to trillions of dollars. (For a discussion of corresponding ‘value of technological innovation’ studies see Edmonds and Smith (2006) and Section 3.4, particularly Figure 3.36 in Chapter 3). However, to date, model calculations offer no guidance on the likelihood or uncertainty of realizing ‘advanced technology’ scenarios. However, there is an increasing number of studies (e.g. Gerlagh and Van der Zwaan, 2006) that explore the mechanisms and policy instruments that would need to be set in place in order to induce such drastic technological changes.
Framing Issues
1400
Cumulative (1990-2100) system cost (trillion 1990US$) 450 ppmv CO2 stabilization
1200
550 ppmv 650 ppmv
1000
550 ppmv 450 ppmv
800
Given the persistent uncertainty of what constitutes ‘dangerous interference with the climate system’ and the resulting uncertainty on ultimate climate stabilization targets, another important finding related to technology economics emerges from the available literature. Differences in the cost of meeting a prescribed CO2 concentration target across alternative technology development pathways that could unfold in the absence of climate policies are more important than cost differences between alternative stabilization levels within a given technology-reference scenario. In other words, the overall ‘reference’ technology pathway can be equally, if not more, important in determining the costs of a given scenario as the stringency of the ultimate climate stabilization target chosen (confer Figure 2.2). In a series of alternative stabilization runs imposed on the SRES A1 scenarios, chosen for ease of comparability as sharing similar energy demands, Roehrl and Riahi (2000) confer also IPCC (2001) have explored the cost differences between four alternative baselines and their corresponding stabilization targets, ranging from 750 ppmv all the way down to 450 ppmv. In their calculations, the cost differences between alternative baselines are also linked to differences in baseline emissions:
750 ppmv A1G
A1C
550 ppmv
A1B
450 ppmv 600
The treatment of technological change in an emissions and climate policy modeling framework can have a huge effect on estimates of the cost of meeting any environmental target. Models in which technological change is dominated by experience (learning) curve effects, show that the cost of stabilizing GHG concentrations could be in the range of a few tenths of a percent of GDP, or even lower (in some models even becoming negative) – a finding also confirmed by other modelling studies (e.g. Rao et al., 2005) and consistent with the results of the study by Gritsevskyi and Nakicenovic (2000) reviewed above, which also showed identical costs of ‘high’ versus ‘low’ long-term emission futures. This contrasts with the traditional view that the long-term costs28 of climate stabilization could be very high, amounting to several percentage points of economic output (see also the review in IPCC, 2001).
750 ppmv
450 ppmv
550 ppmv Alternative baselines
A1T 400
0
1000
3000
5000
7000
9000
Cumulative emissions (GtCO2)
Figure 2.2: The impacts of different technology assumptions on energy systems costs and emissions (cumulative 1990–2100, systems costs (undiscounted) in trillion US$) in no-climate policy baseline (reference) scenarios (based on the SRES A1 scenario family that share identical population and GDP growth assumptions) and in illustrative stabilization scenarios (750, 650, 550 and 450 ppm respectively). For comparison: the total cumulative (undiscounted) GDP of the scenarios is around 30,000 trillion US$ over the 1990–2100 time period. Source: Roehrl and Riahi (2000).
advanced post-fossil fuel technologies yield both lower overall systems costs as well as lower baseline emissions and hence lower costs of meeting a specified climate target (confer the differences between the A1C and A1T scenarios in Figure 2.2). Their findings are consistent with the pattern identified by Edmonds et al. (1997) and Gerlagh and Van der Zwaan (2003). Cost differences are generally much larger between alternative technology baselines, characterized by differing assumptions concerning availability and costs of technologies, rather than between alternative stabilization levels. The IEA (2004) World Energy Outlook also confirms this conclusion, and highlights the differential investment patterns entailed by alternative technological pathways.29 The results from the available literature thus confirm the value of advances in technology importance in lowering future ‘baseline’ emissions in order to enhance feasibility, flexibility, and economics of meeting alternative stabilization targets, in lowering overall systems costs, as well as in lowering the costs of meeting alternative stabilization targets. A robust analytical finding arising from detailed technologyspecific studies is that the economic benefits of technology improvements (i.e. from cost reductions) are highly non-linear, arising from the cumulative nature of technological change, from interdependence and spillover effects, and from potential
28 Note here that this statement only refers to the (very) long term, i.e. a time horizon in which existing capital stock and technologies will have been turned over and replaced by newer vintages. In the short term (and using currently or near-term available technologies) the costs of climate policy scenarios are invariably higher than their unconstrained counterparts. 29 The IEA (2004) ‘alternative scenario’, while having comparable total systems costs, would entail an important shift in investments away from fossil-fuel-intensive energy supply options towards energy efficiency improvements, a pattern also identified in the scenario study of Nakicenovic et al. (1998b).
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increasing returns to adoption (i.e. costs decline with increasing market deployment of a given technology).30 (A detailed review covering the multitude of sources of technological change, including the aforementioned effects, is provided in Chapter 11, Section 11.5, discussing so-called ‘induced technological change’ models). 2.7.2
Technological change
Changes in technology do not arise autonomously – they arise through the actions of human beings, and different social and economic systems have different proclivities to induce technological change. The range of actors participating in the process of technological change spans the full range of those that use technology, design and manufacture technology, and create new knowledge. The process of technological change has several defining characteristics. First, the process is highly uncertain and unpredictable. Firms planning research toward a well-defined technical goal must plan without full knowledge regarding the potential cost, time frame, and even the ultimate success. Further, the history of technological development is rife with small and large examples of serendipitous discoveries, (e.g. Teflon) whose application is far beyond, or different, than their intended use. A second defining characteristic of technological change is the transferable, public-good nature of knowledge. Once created, the value of technological knowledge is difficult to fully appropriate; some or all eventually spills over to others, and in doing so the knowledge is not depleted. This characteristic of knowledge has both benefits and drawbacks. On the one hand, an important discovery by a single individual, such as penicillin, can be utilized worldwide. Knowledge of penicillin is a public good and therefore one person’s use of this knowledge does not preclude another person from using this same knowledge – unlike for capital or labour, where use in one task precludes use in an alternative task. On the other hand, the understanding by potential innovators that any new knowledge might eventually spill over to others limits expected profits and therefore dampens private-sector innovative activity. Thus intellectual property rights can serve both as a barrier and an aid in technology change. A final, third feature of technological change is its cumulativeness, which is also frequently related to spillover effects. There are numerous paradigms used to separate the process of technological change into distinct phases. One approach is to consider technological change as roughly a two-part process,
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which includes: (1) The process of conceiving, creating, and developing new technologies or enhancing existing technologies – the process of advancing the ‘technological frontier’. (2) The process of diffusing or deploying these technologies. These two processes are inextricably tied. The set of available technology defines what might be deployed, and the use of technology affords learning that can guide R&D programmes or directly improve technology through learning-by-doing. The two processes are also linked temporally. The set of technologies that find their way into use necessarily lags the technological frontier. The useful life of technologies – their natural turnover rate – helps to drive the time relationship. Car lifespans can be in the order of 15 years, but the associated infrastructure – roads, filling stations, vehicle manufacturing facilities – have significantly longer lifespans, and electric power plants may be used for a half-century or more; hence, the average car is substantially younger than the average coal-fired power plant and much of its associated infrastructure. The nature of the capital stock (e.g. flexifuel cars that can use both conventional petrol and ethanol) is also important in determining diffusion speed. 2.7.2.1
The sources of technological change
New technology arises from a range of interacting drivers. The literature (for a review see, for example, Freeman, 1994, and Grubler, 1998) divides these drivers into three broad, overlapping categories: R&D, learning-by-doing, and spillovers. These drivers are distinctly different31 from other mechanisms that influence the costs of a given technology, such as. through economies of scale effects (see Box 2.3 below). Each of these entails different agents, investment needs, financial institutions and is affected by the policy environment. These are briefly discussed below, followed by a discussion of the empirical evidence supporting the importance of these sources and the linkages between them. Research and Development (R&D): R&D encompasses a broad set of activities in which firms, governments, or other entities expend resources specifically to improve technology or gain new knowledge. While R&D covers a broad continuum, it is often parsed into two categories: applied R&D and fundamental research, and entails both science and engineering (and requires science and engineering education). Applied R&D focuses on improving specific, well-defined technologies (e.g. fuel cells). Fundamental research focuses on broader and more fundamental areas of understanding. Fundamental research may be mission-oriented (e.g. fundamental biological research
30 This is frequently referred to as a ‘learning-by-doing’ phenomenon. However, the linkages between technology costs and market deployment are complex, covering a whole host of influencing factors including (traditional) economics of larger market size, economies of scale in manufacturing, innovation-driven technology improvements, geographical and inter-industry spillover effects, as well as learning-by-doing (experience curve) phenomena proper. For (one of the few available) empirical studies analyzing the relative contribution of their various effects on cost improvements see Nemet (2005). A more detailed discussion is provided in Chapter 11. 31 However, there are important relations between economies of scale and technological change in terms that scaling up usually also requires changes in manufacturing technologies, even if the technology manufactured remains unchanged.
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intended to provide a long-term knowledge base to fight cancer or create fuels) or focus on new knowledge creation without explicit consideration of use (see Stokes (1997) regarding this distinction). Both applied R&D and fundamental research are interactive: fundamental research in a range of disciplines or research areas, from materials to high-speed computing, can create a pool of knowledge and ideas that might then be further developed through applied R&D. Obstacles in applied R&D can also feed research priorities back to fundamental research. As a rule of thumb, the private sector takes an increasingly prominent role in the R&D enterprise the further along the process toward commercial application. Similar terms found in the literature include: Research, Development, and Demonstration (RD&D), and Research, Development, Demonstration, and Deployment (RDD&D or RD3). These concepts highlight the importance of linking basic and applied research to initial applications of new technologies that are an important feedback and learning mechanism for R&D proper. R&D from across the economic spectrum is important to climate change. Energy-focused R&D, basic or applied, as well as R&D in other climate-relevant sectors (e.g. agriculture) can directly influence the greenhouse gas emissions associated with these sectors (CO2, CH4). At the same time, R&D in seemingly unrelated sectors may also provide spillover benefits to climaterelevant sectors. For example, advances in computers over the last several decades have enhanced the performance of the majority of energy production and use technologies. Learning-by-doing: Learning-by-doing refers to the technology-advancing benefits that arise through the use or production of technology, i.e. market deployment. The more that an individual or an organization repeats a task, the more adept or efficient that organization or individual becomes at that task. In early descriptions (for example, Wright, 1936), learningby-doing referred to improvements in manufacturing labour productivity for a single product and production line. Over time, the application of learning-by-doing has been expanded to the level of larger-scale organizations, such as an entire firm producing a particular product. Improvements in coordination, scheduling, design, material inputs, and manufacturing technologies can increase labour productivity, and this broader definition of learning-by-doing therefore reflects experience gained at all levels in the organization, including engineering, management, and even sales and marketing (see, Hirsh, 1956; Baloff, 1966; Yelle, 1979; Montgomery and Day, 1985; Argote and Epple, 1990). There are clearly important interactions between learningby-doing and R&D. The production and use of technologies provides important feedbacks to the R&D process, identifying key areas for improvement or important roadblocks. In addition, the distinction between learning-by-doing and R&D is blurred at the edges: for example, everyday technology design improvements lie at the boundary of these two processes.
Framing Issues
Spillovers: Spillovers refer to the transfer of knowledge or the economic benefits of innovation from one individual, firm, industry, or other entity to another. The gas turbine in electricity production, 3-D seismic imaging in oil exploration, oil platform technologies and wave energy, and computers are all spillovers in a range of energy technologies. For each of these obvious cases of spillovers there are also innumerable, more subtle instances. The ability to identify and exploit advances in unrelated fields is one of the prime drivers of innovation and improvement. Such advances draw from an enabling environment that supports education, research and industrial capacity. There are several dimensions to spillovers. Spillovers can occur between: (1) Firms within an industry in and within countries (intraindustry spillovers). (2) Industries (inter-industry spillovers). (3) Countries (international spillovers). The latter have received considerable attention in the climate literature (e.g. Grubb et al., 2002). Spillovers create a positive externality for the recipient industry, sector or country, but also limit (but not eliminate) the ability of those that create new knowledge to appropriate the economic returns from their efforts, which can reduce private incentives to invest in technological advance (see Arrow, 1962), and is cited as a primary justification for government intervention in markets for innovation. Spillovers are not necessarily free. The benefits of spillovers may require effort on the part of the receiving firms, industries, or countries. Explicit effort is often required to exploit knowledge that spills over, whether that knowledge is an explicit industrial process or new knowledge from the foundations of science (see Cohen and Levinthal, 1989). The opportunities created by spillovers are one of the primary sources of knowledge that underlies innovation (see Klevorick, et al., 1995). There are different channels by which innovativions may spillover. For instance, the productivity achieved by a firm or an industry depends not only on its own R&D effort, but also on the pool of general knowledge to which it has access. There are also so-called ‘rent spillovers’, such as R&D leading to quality changes embodied in new and improved outputs which not necessarily yield higher prices. Finally, spillovers are frequent for products with high market rivalry effects (e.g. through reverse engineering or industrial espionage). However it is inherently difficult to distinguish clearly between these various channels of spillovers. Over the last half century, a substantial empirical literature has developed, outside the climate or energy contexts, which explores the sources of technological advance. Because of the complexity of technological advance and the sizable range of forces and actors involved, this literature has proceeded largely through partial views, considering one or a small number of sources, or one or a small number of technologies. On the whole, the evidence strongly suggests that all three of the 153
Framing Issues
Chapter 2
Box 2.3 Economies of scale Economies of scale refer to the decreases in the average cost of production that come with an increase in production levels, assuming a constant level of technology. Economies of scale may arise, for example, because of fixed production costs that can be spread over larger and larger quantities as production increases, thereby decreasing average costs. Economies of scale are not a source of technological advance, but rather a characteristic of production. However, the two concepts are often intertwined, as increased production levels can bring down costs both through learning-by-doing and economies of scale. It is for this reason that economies of scale have often been used as a justification for using experience curves or learning curves in integrated assessment models.
sources highlighted above – R&D, learning-by-doing, and spillovers – play important roles in technological advance and there is no compelling reason to believe that one is broadly more important than the others. The evidence also suggests that these sources are not simply substitutes, but may have highly complementary interactions. For example, learning from producing and using technologies provides important market and technical information that can guide both public and private R&D efforts. Beginning with Griliches’s study of hybrid corn (see Griliches, 1992), economists have conducted econometric studies linking R&D to productivity (see Griliches, 1992, Nadiri, 1993, and the Australian Industry Commission, 1995 for reviews of this literature). These studies have used a wide range of methodologies and have explored both public and private R&D in several countries. As a body of work, the literature strongly suggests substantial returns from R&D, social rates well above private rates in the case of private R&D (implying that firms are unable to fully appropriate the benefits of their R&D), and large spillover benefits. Griliches (1992) writes that ‘… there have been a significant number of reasonably well done studies all pointing in the same direction: R&D spillovers are present, their magnitude may be quite large, and social rates of return remain significantly above private rates’. Since at least the mid-1930s (see Wright, 1936), researchers have also conducted statistical analyses on ‘learning curves’ correlating increasing cumulative production volumes and technological advance. Early studies focused heavily on military applications, notably wartime ship and airframe manufacture (see Alchian, 1963 and Rapping, 1965). From 1970 through to the mid-1980s, use of experience curves was widely recommended for corporate strategy development. More recently, statistical analyses have been applied to emerging energy technologies such as wind and solar power. (Good summaries of the experience curve literature can be found in Yelle, 1979; Dutton and Thomas, 1984. Energy technology experience curves may be found in Zimmerman, 1982; Joskow and Rose, 1982; Christiansson, 1995; McDonald and Schrattenholzer, 2001). Based on the strength of these correlations, large-scale energy and environmental models are increasingly using ‘experience curves’ or ‘learning curves’ to capture the response of technologies to increasing use (e.g. Messner, 1997; IEA, 154
2000; Rao et al., 2005; and the review by Clarke and Weyant, 2002). These curves correlate cumulative production volume to per-unit costs or other measures of technological advance. An important methodological issue arising in the use of these curves is that the statistical correlations on which they are based do not address the causal relationships underlying the correlations between cumulative production and declining costs, and few studies address the uncertainties inherent in any learning phenomenon (including negative learning). Because these curves often consider technologies over long time frames and many stages of technology evolution, they must incorporate the full range of sources that might affect technological advance or costs and performance more generally, including economies of scale, changes in industry structure, own-industry R&D, and spillovers from other industries and from government R&D. Together, these sources of advance reduce costs, open up larger markets, and result in increasing cumulative volume (see Ghemawat, 1985; Day and Montgomery, 1983; Alberts, 1989; Soderholm and Sundqvist, 2003). Hence, the causal relationships necessarily operate both from cumulative volume to technological advance and from technological advance to cumulative volume. A number of studies have attempted to probe more deeply into the sources of advance underlying these correlations (see, for example, Rapping, 1965; Lieberman, 1984; Hirsh, 1956; Zimmerman, 1982; Joskow and Rose, 1985; Soderholm and Sundqvist, 2003, and Nemet, 2005). On the whole, these studies continue to support the presence of learning-by-doing effects, but also make clear that other sources can also be important and can influence the learning rate. This conclusion is also confirmed by recent studies following a so-called ‘twofactor-learning-curve’ hypothesis that incorporates both R&D and cumulative production volume as drivers of technological advance within a production function framework (see, for example, Kouvaritakis et al., 2000). However, Soderholm and Sundqvist (2003) conclude that ‘the problem of omitted variable bias needs to be taken seriously’ in this type of approach, in addition to empirical difficulties that arise, because of the absence of public and private sector technology-specific R&D statistics and due to significant co-linearity and auto-correlation of parameters (e.g. Miketa and Schrattenholzer, 2004).
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More broadly, these studies, along with related theoretical work, suggest the need for further exploration of the drivers behind technological advance and the need to develop more explicit models of the interactions between sources. For example, while the two-factor-learning-curves include both R&D and cumulative volume as drivers, they often assume a substitutability of the two forms of knowledge generation that is at odds with the (by now widely accepted) importance of feedback effects between ‘supply push’ and ‘demand pull’ drivers of technological change (compare Freeman, 1994). Hence, while modelling paradigms such as two-factor-learningcurves might be valuable methodological steps on the modelling front, they remain largely exploratory. For a (critical) discussion and suggestion for an alternative approach see, for example, Otto et al., 2005. A range of additional lines of research has explored the sources of technological advance. Authors have pursued the impacts of ‘general-purpose technologies’, such as rotary motion (Bresnahan and Trajtenberg, 1992), electricity and electric motors (Rosenberg, 1982), chemical engineering (Rosenberg, 1998), and binary logic and computers (Bresnahan and Trajtenberg, 1992). Klevorick et al. (1995) explored the sources of technological opportunity that firms exploit in advancing technology, finding important roles for a range of knowledge sources, depending on the industry and the application. A number of authors (see, for example, Jaffe and Palmer 1996; Lanjouw and Mody 1996; Taylor et al., 2003; Brunnermier and Cohen, 2003; Newell et al. 1998) have explored the empirical link between environmental regulation and technological advance in environmental technologies. This body of literature indicates an important relationship between environmental regulation and innovative activity on environmental technologies. On the other hand, this literature also indicates that not all technological advance can be attributed to the response to environmental regulation. Finally, there has been a long line of empirical research exploring whether technological advance is induced primarily through the appearance of new technological opportunities (technology-push) or through the response to perceived market demand (market pull). (See, for example, Schmookler, 1962; Langrish et al., 1972; Myers and Marquis, 1969; Mowery and Rosenberg, 1979; Rosenberg 1982; Mowery and Rosenberg, 1989; Utterback, 1996; Rycroft and Kash 1999). Over time, a consensus has emerged that ‘the old debate about the relative relevance of “technology push” versus “market pull” in delivering new products and processes has become an anachronism. In many cases one cannot say with confidence that either breakthroughs in research “cause” commercial success or that the generation of successful products or processes was a predictable “effect” of having the capability to read user demands or other market signals accurately’ (Rycroft and Kash, 1999).
Framing Issues
2.7.2.2
Development and commercialization: drivers, barriers and opportunities
Development and diffusion or commercialization of new technology is largely a private-sector endeavour driven by market incentives. The public sector can play an important role in coordination and co-funding of these activities and (through policies) in structuring market incentives. Firms choose to develop and deploy new technologies to gain market advantages that lead to greater profits. Technological change comprises a whole host of activities that include R&D, innovations, demonstration projects, commercial deployment and widespread use, and involves a wide range of actors ranging from academic scientists and engineers, to industrial research labs, consultants, firms, regulators, suppliers and customers. When creating and disseminating revolutionary (currently non-existent) technologies, the path to development may proceed sequentially through the various phases, but for existing technology, interactions can occur between all phases, for example, studies of limitations in currently deployed technologies may spark innovation in fundamental academic research. The ability to identify and exploit advances in unrelated fields (advanced diagnostics and probes, computer monitoring and modelling, control systems, materials and fabrication) is one of the prime drivers of innovation and improvement. Such advances draw from an enabling environment that supports education, research and industrial capacity. The behaviour of competing firms plays a key role in the innovation process. Especially in their efforts to develop and introduce new non-commercial technology into a sustainable commercial operations, firms require not only the ability to innovate and to finance costly hardware, but also the managerial and technical skills to operate them and successfully market the products, particularly in the early stages of deployment and diffusion. The development of proprietary intellectual property and managerial know-how are key ingredients in establishing competitive advantage with new technology, but they can be costly and difficult to sustain. Several factors must therefore be considered prominently with respect to the process of technology development and commercialization. A detailed review of these factors is included in the IPCC Special Report on Technology Transfer (SRTT) and the discussion below provides a summary and update, which draws on Flannery and Khesghi (2005) and OECD (2006). Factors to consider in development and commercialization of new technologies include: • First, the lengthy timescale for deployment of advanced energy technologies. • Second, the range of barriers that innovative technologies must successfully overcome if they are to enter into widespread commercial use.
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• Third, the role of governments in creating an enabling framework to enhance the dissemination of innovative commercial technology created by private companies. • Fourth, absorptive capacity and technological capabilities are also important determinants of innovation and diffusion. New technologies must overcome a range of technical and market hurdles to enter into widespread commercial use. Important factors include: • Performance. • Cost. • Consumer acceptance. • Safety. • Financial risks, available financing instruments. • Enabling infrastructure. • Incentive structures for firms (e.g. licensing fees, royalties, policy environment, etc.). • Regulatory compliance. • Environmental impacts. The diffusion potential for a new technology depends on all above factors. If a technology fails even in one of these dimensions it will not achieve significant global penetration. While reducing greenhouse gas emissions should be an important objective in technological research, it is not the only factor. Another factor is that the lengthy timescale for deployment of advanced energy technologies has a substantive impact on private-sector behaviour. Even with successful innovation in energy technology, the time necessary for new technology to make a widespread global impact on emissions will be lengthy. Timescales are long, both due to the long lifespan of existing productive capital stock, and the major investment in hardware and infrastructure that is required for significant market penetration. During the time that advanced technology is being deployed, both incremental and revolutionary changes may occur in the technologies under consideration, and in those that compete with them. One consequence of the long time scales involved with energy technology is that, at any point in time, there will inevitably be a significant spread in the efficiency and performance of the existing equipment deployed. While this presents an opportunity for advanced technology to reduce emissions, the overall investment required to prematurely replace a significant fraction of sunk capital can be prohibitive. Another consequence of the long time scale and high cost of equipment is that it is difficult to discern long-term technological winners and losers in evolving markets. A third factor is enabling infrastructure. Infrastructure can be interpreted broadly. Key features have been described in
Chapter 2
numerous studies and assessments (e.g. IPIECA, 1995), and include: rule of law, safety, secure living environment for workers and communities, open markets, realization of mutual benefits, protection of intellectual property, movement of goods, capital and people, and respect for the needs of host governments and communities. These conditions are not unique for private companies. Many of them also are essential for successful public investment in technology and infrastructure.32 2.7.2.3
The public-sector role in technological change
Given the importance of technology in determining both the magnitude of future GHG emission levels as well as feasibility and costs of emission reduction efforts, technology policy considerations are increasingly considered in climate policy analyses. Ongoing debate centers on the relative importance of two differing policy approaches: technology-push (through efforts to stimulate research and development) and demand-pull (through measures that demand reduced emissions or enhanced efficiency). Technology-push emphasizes the role of policies that stimulate research and development, especially those aimed at lowering the costs of meeting long-term objectives with technology that today is very far from economic in existing markets. This might include such measures as publicfunded R&D or R&D tax credits. Demand-pull emphasizes the use of instruments to enhance the demand for lower-emission technologies, thereby increasing private incentives to improve these technologies and inducing any learning-by-doing effects. Demand-pull instruments might include emissions taxes or more direct approaches, such as renewable portfolio standards, adoption subsidies, or direct public-sector investments (see Figure 2.3). Two market failures are at issue when developing policies to stimulate technology development. The first is the failure to internalize the environmental costs of climate change, reducing the demand for climate-friendly technologies and thereby reducing private-sector innovation incentives and learning-bydoing. The second is a broad suite of private-sector innovation market failures that hold back and otherwise distort privatesector investment in technological advance, irrespective of environmental concerns (confer Jaffe et al., 2005). Chief among these is the inability to appropriate the benefits of knowledge creation. From an economic standpoint, two market failures require two policy instruments: addressing two market failures with a single instrument will only lead to second-best solutions (see, for example, Goulder and Schneider, 1999). Hence, it is well understood that the optimal policy approach should include both technology-push and demand-pull instruments. While patents and various intellectual property protection (e.g. proprietary know-how) seeks to reward innovators, such protection is inherently imperfect, especially in global markets where such protections are not uniformly enforced by all governments.
32 These and other issues required for successful dissemination of technology were the subject of an entire IPCC Special Report (IPCC, 2000)
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Public sector incentives, standards, regulation, subsidies, taxes
funding
Learning From: Disembodied Technology (Knowledge)
Basic R&D
Market DemandPull Pull Market //Demand
Applied R&D
Demonstration
Niche markets
Diffusion
To: Embodied Technology (plant, equipment,..)
Product TechnologyPush Push Product //Technology
funding
investments, knowledge and market spillovers
Private sector Figure 2.3 : Technology development cycle and its main driving forces. Note that important overlaps and feedbacks exist between the stylized technology life-cycle phases illustrated here and therefore the illustration does not suggest a ‘linear’ model of innovation. Source: Adapted from Foxon (2003) and Grubb (2005).
Similarly, in the early adoption of technology learning-bydoing (by producers) or learning-by-using (by consumers) may lower the cost to all future users, but in a way that may not fully reward the frontrunners.33 Similarly, lack of information by investors and potential consumers of innovative technologies may slow the diffusion of technologies into markets. The ‘huge uncertainties surrounding the future impacts of climate change, the magnitude of the policy response, and thus the likely returns to R&D investment’ exacerbate these technological spillover problems (Jaffe et al., 2005). The outstanding questions revolve around the relative combinations of instruments and around how effective singlepolicy approaches might be. Within this context, a number of authors (e.g. Montgomery and Smith, 2005) have argued that fundamental long-term shifts in technology to mitigate greenhouse gas emissions cannot be achieved through emissions-constraining policies alone, and short-term cap and trade emission-reduction policies provide insufficient incentives for R&D into long-term technology options. Conversely, Popp (2002) demonstrated how energy R&D is responsive to price signals, suggesting that without emissions constraints R&D into new low-emission technologies may face a serious lack of incentives and credible policy signals. The argument that emissions-based policies will induce long-term technology
innovation relies primarily on two lines of reasoning (Goulder 2004; Grubb, 2005). The first is that the anticipation of future targets, based on a so-called announcement effect, will stimulate firms to invest in research and development and ultimately to invest in advanced, currently non-commercial technology (the credibility and effectiveness of this effect, however, being challenged by Montgomery and Smith, 2005). The second is that early investment, perhaps through incentives, mandates, or government procurement programmes, will initiate a cycle of learning-by-doing that will ultimately promote innovation in the form of continuous improvement, which will drive down the cost of future investments in these technologies. This issue is especially critical in the scaling up of niche-market applications of new technologies (e.g. renewables) where mobilizing finance and lowering investment risks are important (see, for example, IEA, 2003, or Hamilton, 2005). In their comparative analysis of alternative policy instruments Goulder and Schneider (1999) found that when comparing a policy with only R&D subsidies to an emissions tax, the emissions-based policies performed substantially better. Irrespective of the mix between demand-pull and technologypush instruments, a number of strong conclusions have emerged with respect to the appropriate policies to stimulate technological advance. First, it is widely understood that flexible, incentive-
33 However, there are many other factors, in addition to appropriating returns from innovation, that influence the incentive structure of firms, including ‘first mover’ advantages, market power, use of complementary assets, etc. (for a review see Levin et al., 1987).
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oriented policies are more likely to foster low-cost compliance pathways than those that impose prescriptive regulatory approaches (Jaffe et al., 2005). A second robust conclusion is the need for public policy to promote a broad portfolio of research, because results cannot be guaranteed since it is impossible to ex ante identify technical winners or losers (GTSP, 2001). A third conclusion is that more than explicit climate change or energy research is critical for the development of technologies pertinent to climate change. Spillovers from non-energy sectors have had enormous impacts on energy-sector innovation, implying that a broad and robust technological base may be as important as applied energy sector or similar R&D efforts. This robust base involves the full ‘national systems of innovation’34 involved in the development and use of technological knowledge. Cost and availability of enabling infrastructure can be especially important factors that limit technology uptake in developing countries.35 Here enabling infrastructure would include management and regulatory capacity, as well as associated hardware and public infrastructure. 2.7.3
The international dimension in technology development and deployment: technology transfer
Article 4.5 of the Convention states that developed country Parties ‘shall take all practicable steps to promote, facilitate, and finance, as appropriate, the transfer of, or access to, environmentally sound technologies and know-how to other Parties, particularly developing country Parties, to enable them to implement the provisions of the Convention’, and to ‘support the development and enhancement of endogenous capacities and technologies of developing country Parties’. Similarly Article 10(c) of the Kyoto Protocol reiterated that all Parties shall: ‘cooperate in the promotion of effective modalities for the development, application, and diffusion of, and take all practicable steps to promote, facilitate and finance, as appropriate, the transfer of, or access to, environmentally sound technologies, know-how, practices and processes pertinent to climate change, in particular to developing countries, including the formulation of policies and programmes for the effective transfer of environmentally sound technologies that are publicly owned or in the public domain and the creation of an enabling environment for the private sector, to promote and enhance the transfer of, and access to, environmentally sound technologies’. Technology transfer is particularly relevant because of the great interest by developing countries in this issue. This interest arises from the fact that many developing countries are in a
Chapter 2
phase of massive infrastructure build up. Delays in technology transfer could therefore lead to a lock-in in high-emissions systems for decades to come (e.g. Zou and Xuyan, 2005). Progress on this matter has usually been linked to progress on other matters of specific interest to developed countries. Thus Article 4.7 of the Convention is categorical that ‘the extent to which developing country Parties will effectively implement their commitments under the Convention will depend on the effective implementation by developed country Parties of their commitments under the Convention related to financial resources and the transfer of technology’. The IPCC Special Report on Methodological and Technological Issues on Technology Transfer (SRTT) (IPCC, 2000) defined the term ‘technology transfer’ as a broad set of processes covering the flows of know-how, experience and equipment for mitigating and adapting to climate change amongst different stakeholders. A recent survey of the literature is provided in Keller (2004) and reviews with special reference to developing countries are included in Philibert (2005) and Lefevre (2005). The definition of technology transfer in the SRTT and the relevant literature is wider than implied by any particular article of the Convention or the Protocol. The term ‘transfer’ was defined to ‘encompass diffusion of technologies and technology cooperation across and within countries’. It also ‘comprises the process of learning to understand, utilize and replicate the technology, including the capacity to choose and adapt to local conditions and integrate it with indigenous technologies’. This IPCC report acknowledged that the ‘theme of technology transfer is highly interdisciplinary and has been approached from a variety of perspectives, including business, law, finance, micro-economics, international trade, international political economy, environment, geography, anthropology, education, communication, and labour studies’. Having defined technology transfer so broadly, the report (IPCC, 2000, p. 17) concluded that ‘although there are numerous frameworks and models put forth to cover different aspects of technology transfer, there are no corresponding overarching theories’ (emphasis added). Consequently there is no framework that encompasses such a broad definition of technology transfer. The aforementioned report identified different stages of technology transfer and different pathways through which it is accomplished. These stages of technology transfer are: identification of needs, choice of technology, and assessment of conditions of transfer, agreement and implementation. Evaluation and adjustment or adaptation to local conditions, and replication are other important stages. Pathways for technology
34 The literature on national innovation systems highlights in particular the institutional dimensions governing the feedback between supply-push and demand-pull, and the interaction between the public and private sectors that are distinctly different across countries. A detailed review of this literature is beyond the scope of this assessment. For an overview see, for example Lundvall, 2002, and Nelson and Nelson, 2002. 35 In this context, the concept of technological ‘leapfrogging’ (Goldemberg, 1991), and the resulting requirements for an enabling environment for radical technological change, is frequently discussed in the literature. For a critical review see, for example, Gallagher (2006).
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enabling/disabling environment, e.g. technology denial regimes
enabling/disabling environment, e.g. international property rights regimes conditions of transfer
ORIGINATOR characteristics
RECIPIENT characteristics
USERS
technology characteristics feedback
Figure 2.4: A general framework for factors affecting technology transfer and subsequent innovation.
transfer vary depending on the sector, technology type and maturity and country circumstances. Given this variety and complexity, the report concluded that there is no pre-set answer to enhancing technology transfer. There is no international database tracking the flow of ESTs (environmentally sound technologies). Little is known about how much climate-relevant equipment is transferred, and even less about the transfer of know-how, practices and processes, and most international analyses rely on proxy variables. It is well known that the nature of financial flows from OECD countries to developing countries has changed over the last 15 years. Overseas development assistance (ODA) has declined and been overtaken by private sources of foreign direct investments (WDI, 2005). International financial statistics only reflect the quantity and not the quality of FDI. They also say nothing about what fraction is a transfer of ESTs. Despite its decline, ODA is still critical for the poorest countries, particularly when it is aimed at developing basic capacities to acquire, adapt, and use foreign technologies. IPCC (2000, p. 22) summarized the historical experience as a ‘failure of top-down, technology-focused development’. Some developing country policymakers believe that payments for technology are beyond their means and that international technology transfer contributes little to technological development in the recipient country (UNDP, 2000). Many failures of technology transfer have resulted from an absence of human and institutional capacity (IPCC, 2000, p. 118). There are several modes to encourage technology transfer to developing countries, from technical assistance and technology grants, to capacity building and policy development cooperation. The priorities for these modes shift as host countries develop economically. Technology demonstration projects can play an important role early in the industrialization process. As the economy grows, policy development cooperation, such as assistance to develop energy-efficiency standards or to create an enabling environment for technology diffusion, becomes
more important. Ohshita and Ortolano (2003) studied past experiences of demonstration projects using cleaner energy technologies in developing countries through assistance by international organizations as well as developed countries. They found that demonstration projects raised awareness of cleaner energy technologies in the technology transfer process, but were not very successful in diffusing the technologies more widely in the target developing countries. For China in particular, demonstration projects played an important role in the past, when the economy began shifting from a centrally planned system to a more open, market-based system. There is increasing recognition that other modes of technology diffusion may now be more suitable for China. Given the continued high growth of the Chinese economy, donors have been shifting their assistance programmes from technology demonstration to policy development assistance (Ohsita, 2006). Figure 2.4 shows one attempt to create a framework for all forms of technology transfer. In all forms technology transfer, especially across countries, at least seven characteristics are important. These are: 1. The characteristics of the technology. 2. The characteristics of the originator of the transfer. 3. The enabling (or disabling) environment in the country of origin. 4. The conditions of the transfer. 5. The characteristics of the recipient. 6. The enabling (or disabling) environment in the host country. 7. The ultimately valuable post-transfer steps, i.e. assimilation, replication and innovation. Each of these characteristics are discussed below. Characteristics of the originator of the transfer. Initially, there was a widespread tendency to think of technology transfer in supply-side terms – the initial choice and acquisition of technology (Brooks, 1995) and a lack of corresponding focus on the other factors that influence the successful outcome of 159
Framing Issues
technology transfer, such as enabling environment, institutions and finance. The environment in the country of origin can be conducive or disabling for technology transfer. The public sector continues to be an important driver in the development of ESTs. Of the 22 barriers listed in the technical summary of the IPCC Report (2000) as barriers to technology transfer, 21 relate to the enabling environment of recipient countries. Many governments transfer or license the patents arising out of publicly funded efforts to the private sector as a part of their industrial policy, and then the transferred patents follow the rules of privately owned technologies (IPCC, 2000, p. 25). One should also consider the ‘imperfect’ nature of technology markets: (1) While some of the components of technology are of a public-good nature, others have an important tacit nature. (2) Technology markets are normally very concentrated on the supply side, and bargaining power is unevenly distributed. (3) The strategic nature of technologies normally includes limiting clauses and other restrictions in transfer contracts (for a discussion see Arora et al., 2001; Kumar, 1998). Technology Denial Regimes36 in the country of origin also sometimes constitute a barrier to technology transfer, especially for multiple-use technologies. Thus supercomputers can be used for climate modelling and global circulation models and also to design missiles. The conditions of the transfer. Most technologies are transferred in such a way that the originators also benefit from the transfer and this helps to establish strong incentives for proper management and maintenance of the technologies. The conditions of the transfer will primarily depend on the transfer pathway used, as mentioned above. Common pathways include government assistance programmes, direct purchases, trade, licensing, foreign direct investment, joint ventures, cooperative research agreements, co-production agreements, education and training and government direct investment. Developing countries have argued for the transfer of ESTs and corresponding know-how, on favourable, concessional and preferential terms (Agenda 21, 1992, Chapter 34). There have been instances in the pharmaceutical industry when certain drugs benefiting developing countries have been licensed either free or on concessionary terms. The characteristics of the recipient. The recipient must understand local needs and demands; and must possess the ability to assess, select, import, adapt, and adopt or utilize appropriate technologies.
Chapter 2
The enabling (or disabling) environment in the host country. Many of the barriers to technology transfer that are listed in the IPCC Report (IPCC, 2000, p. 19) relate to the lack of an enabling (or a disabling) environment in the recipient country for the transfer of ESTs. A shift in focus, from technology transfer per se to the framework represented in Figure 2.4, leads to an equal emphasis on the human and institutional capacity in the receiving country. A crucial dimension of the enabling environment is an adequate science and educational infrastructure. It must be recognized that capacity building to develop this infrastructure is a slow and complex process, to which long-term commitments are essential. A recipient’s ability to absorb and use new technology effectively also improves its ability to develop innovations. Unfortunately, the capacity to innovate and replicate is poorly developed in developing countries (STAP, 1996). However, the engineering and management skills required in acquiring the capacity to optimize and innovate are non-trivial. The technology-importing firm needs to display what has been called ‘active technological behaviour’. Firms that do not do this are left in a vicious circle of technological dependence and stagnation (UNDP, 2000).
2.8
Climate change studies have used various different regional definitions depending on the character of the problem considered and differences in methodological approaches. Regional studies can be organized according to geographical criteria, political organizational structures, trade relations, climatic conditions, stage of industrialization or other socio-economic criteria relevant to adaptive and mitigative capacity (Duque and Ramos, 2004; Ott et al., 2004; Pan, 2004a). Some classifications are based on so-called ‘normative criteria’ such as membership of countries in UN fora and agreements. Differentiation into Annex-1 and non-Annex1 countries is specified in the UNFCCC, although the classification of certain countries has been a matter of some dispute. Annex-1 countries are further sub-divided into those that are undergoing a transition to market economies. Figure 13.2 in Chapter 13 shows the current country groupings under the Climate Convention, OECD and the European Union. Some Economies in Transition (Rabinovitch and Leitman, 1993) and developing countries are members of the OECD, and some developing countries have income levels that are higher than developed nations (Baumert et al., 2004; Ott et al., 2004). Given the complexities of the criteria used in country groupings, in this report the terms ‘developed countries’, ‘economies in
36 Regulatory criteria denying access to certain technologies to individual countries or groups of countries.
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Framing Issues
transition’ (together forming the industrialized countries) and ‘developing countries’ are commonly used; categories that are primarily of a socio-economic nature. In climate mitigation studies, there are often two types of regional breakdowns used – physio-geographic or socioeconomic. Data on insolation (relevant to solar power), rainfall (relevant to hydrower), temperature, precipitation and soil type (relevant to the potential for carbon sequestration) are examples of physio-geographic classifications useful in climate change mitigation studies. The multitude of possible regional representations hinders the comparability and transfer of information between the various types of studies implemented for specific regions and scales. Data availability also determines what kinds of aggregation are possible. Proxies are used when data is not available. This report has generally chosen a pragmatic way of analyzing regional information and presenting findings. Readers should bear in mind that any regional classification masks sub-regional differences.
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Framing Issues
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3 Issues related to mitigation in the long-term context
Coordinating Lead Authors: Brian Fisher (Australia), Nebojsa Nakicenovic (Austria/Montenegro)
Lead Authors: Knut Alfsen (Norway), Jan Corfee Morlot (France/USA), Francisco de la Chesnaye (USA), Jean-Charles Hourcade (France), Kejun Jiang (China), Mikiko Kainuma (Japan), Emilio La Rovere (Brazil), Anna Matysek (Australia), Ashish Rana (India), Keywan Riahi (Austria), Richard Richels (USA), Steven Rose (USA), Detlef Van Vuuren (The Netherlands), Rachel Warren (UK)
Contributing Authors: Phillipe Ambrosi (France), Fatih Birol (Turkey), Daniel Bouille (Argentina), Christa Clapp (USA), Bas Eickhout (The Netherlands), Tatsuya Hanaoka (Japan), Michael D. Mastrandrea (USA), Yuzuru Matsuoko (Japan), Brian O’Neill (USA), Hugh Pitcher (USA), Shilpa Rao (India), Ferenc Toth (Hungary)
Review Editors: John Weyant (USA), Mustafa Babiker (Kuwait)
This chapter should be cited as: Fisher, B.S., N. Nakicenovic, K. Alfsen, J. Corfee Morlot, F. de la Chesnaye, J.-Ch. Hourcade, K. Jiang, M. Kainuma, E. La Rovere, A. Matysek, A. Rana, K. Riahi, R. Richels, S. Rose, D. van Vuuren, R. Warren, 2007: Issues related to mitigation in the long term context, In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Inter-governmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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Chapter 3
Table of Contents Executive Summary ................................................... 171 3.1
3.5
Emissions scenarios ....................................... 174 3.1.1
The definition and purpose of scenarios ........... 174
3.1.2
Introduction to mitigation and stabilization scenarios ........................................................ 175
3.5.1
The interaction between mitigation and adaptation, an iterative climate policy process ................... 225
3.1.3
Development trends and the lock-in effect of infrastructure choices ...................................... 176
3.5.2
3.1.4
Economic growth and convergence ................. 176
Linking emission scenarios to changes in global mean temperature, impacts and key vulnerabilities .................................................. 227
3.1.5
Development pathways and GHG emissions .... 177
3.5.3
Information for integrated assessment of response strategies ......................................... 229
3.1.6
Institutional frameworks................................... 178
3.6 3.2
3.3
3.4
170
Interaction between mitigation and adaptation, in the light of climate change impacts and decision-making under longterm uncertainty .............................................. 225
Baseline scenarios ........................................... 178 3.2.1
Drivers of emissions ........................................ 178
3.2.2
Emissions ....................................................... 186
Links between short-term emissions trends, envisaged policies and long-term climate policy targets...................................... 233 3.6.1
Insights into the choice of a short-term hedging strategy in the context of long-term uncertainty ...................................................... 234
3.6.2
Evaluation of short-term mitigation opportunities in long-term stabilization scenarios .................. 235
Mitigation scenarios ......................................... 194 3.3.1
Introduction..................................................... 194
3.3.2
Definition of a stabilization target ..................... 194
3.3.3
How to define substitution among gases ......... 195
3.3.4
Emission pathways.......................................... 196
3.3.5
Long-term stabilization scenarios .................... 197
3.3.6
Characteristics of regional and national mitigation scenarios ........................................................ 214
The role of technologies in long-term mitigation and stabilization: research, development, deployment, diffusion and transfer .............................................................. 218 3.4.1
Carbon-free energy and decarbonization ......... 219
3.4.2
RD&D and investment patterns ........................ 222
3.4.3
Dynamics and drivers of technological change, barriers (timing of technology deployment, learning) .......................................................... 222
References..................................................................... 240
Chapter 3
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EXECUTIVE SUMMARY This chapter documents baseline and stabilization scenarios in the literature since the publication of the IPCC Special Report on Emissions Scenarios (SRES) (Nakicenovic et al., 2000) and Third Assessment Report (TAR, Morita et al., 2001). It reviews the use of the SRES reference and TAR stabilization scenarios and compares them with new scenarios that have been developed during the past five years. Of special relevance is how ranges published for driving forces and emissions in the newer literature compare with those used in the TAR, SRES and pre-SRES scenarios. This chapter focuses particularly on the scenarios that stabilize atmospheric concentrations of greenhouse gases (GHGs). The multi-gas stabilization scenarios represent a significant change in the new literature compared to the TAR, which focused mostly on carbon dioxide (CO2) emissions. They also explore lower levels and a wider range of stabilization than in the TAR. The foremost finding from the comparison of the SRES and new scenarios in the literature is that the ranges of main driving forces and emissions have not changed very much (high agreement, much evidence). Overall, the emission ranges from scenarios without climate policy reported before and after the SRES have not changed appreciably. Some changes are noted for population and economic growth assumptions. Population scenarios from major demographic institutions are lower than they were at the time of the SRES, but so far they have not been fully implemented in the emissions scenarios in the literature. All other factors being equal, lower population projections are likely to result in lower emissions. However, in the scenarios that used lower projections, changes in other drivers of emissions have offset their impact. Regional medium-term (2030) economic projections for some developing country regions are currently lower than the highest scenarios used in the SRES. Otherwise, economic growth perspectives have not changed much, even though they are among the most intensely debated aspects of the SRES scenarios. In terms of emissions, the most noticeable changes occurred for projections of SOx and NOx emissions. As short-term trends have moved down, the range of projections for both is currently lower than the range published before the SRES. A small number of new scenarios have begun to explore emission pathways for black and organic carbon. Baseline land-related CO2 and non-CO2 GHG emissions remain significant, with continued but slowing land conversion and increased use of high-emitting agricultural intensification practices due to rising global food demand and shifts in dietary preferences towards meat consumption. The postSRES scenarios suggest a degree of agreement that the decline in annual land-use change carbon emissions will, over time, be less dramatic (slower) than those suggested by many of the SRES scenarios. Global long-term land-use scenarios are scarce in numbers but growing, with the majority of the new literature since the SRES contributing new forestry and
biomass scenarios. However, the explicit modelling of land-use in long-term global scenarios is still relatively immature, with significant opportunities for improvement. In the debate on the use of exchange rates, market exchange rates (MER) or purchasing power parities (PPP), evidence from the limited number of new PPP-based studies indicates that the choice of metric for gross domestic product (GDP), MER or PPP, does not appreciably affect the projected emissions, when metrics are used consistently. The differences, if any, are small compared to the uncertainties caused by assumptions on other parameters, e.g. technological change (high agreement, much evidence). The numerical expression of GDP clearly depends on conversion measures; thus GDP expressed in PPP will deviate from GDP expressed in MER, more so for developing countries. The choice of conversion factor (MER or PPP) depends on the type of analysis or comparison being undertaken. However, when it comes to calculating emissions (or other physical measures, such as energy), the choice between MER-based or PPP-based representations of GDP should not matter, since emission intensities will change (in a compensating manner) when the GDP numbers change. Thus, if a consistent set of metrics is employed, the choice of MER or PPP should not appreciably affect the final emission levels (high agreement, medium evidence). This supports the SRES in the sense that the use of MER or PPP does not, in itself, lead to significantly different emission projections outside the range of the literature (high agreement, much evidence). In the case of the SRES, the emissions trajectories were the same whether economic activities in the four scenario families were measured in MER or PPP. Some studies find differences in emission levels between using PPP-based and MER-based estimates. These results critically depend on, among other things, convergence assumptions (high agreement, medium evidence). In some of the short-term scenarios (with a horizon to 2030) a ‘bottomup’ approach is taken, where assumptions about productivity growth and investment and saving decisions are the main drivers of growth in the models. In long-term scenario models, a ‘top-down’ approach is more commonly used, where the actual growth rates are more directly prescribed based on convergence or other assumptions about long-term growth potentials. Different results can also be due to inconsistencies in adjusting the metrics of energy efficiency improvement when moving from MER-based to PPP-based calculations. There is a clear and strong correlation between the CO2-equivalent concentrations (or radiative forcing) of the published studies and the CO2-only concentrations by 2100, because CO2 is the most important contributor to radiative forcing. Based on this relationship, to facilitate scenario comparison and assessment, stabilization scenarios (both multigas and CO2-only studies) have been grouped in this chapter into different categories that vary in the stringency of the targets, from 171
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low to high radiative forcing, CO2-equivalent concentrations and CO2-only concentrations by 2100, respectively. Essentially, any specific concentration or radiative forcing target, from the lowest to the highest, requires emissions to eventually fall to very low levels as the removal processes of the ocean and terrestrial systems saturate. For low to medium targets, this would need to occur during this century, but higher stabilization targets can push back the timing of such reductions to beyond 2100. However, to reach a given stabilization target, emissions must ultimately be reduced well below current levels. For achievement of the very low stabilization targets from many high baseline scenarios, negative net emissions are required towards the end of the century. Mitigation efforts over the next two or three decades will have a large impact on opportunities to achieve lower stabilization levels (high agreement, much evidence). The timing of emission reductions depends on the stringency of the stabilization target. Lowest stabilization targets require an earlier peak of CO2 and CO2-equivalent emissions. In the majority of the scenarios in the most stringent stabilization category (a stabilization level below 490 ppmv CO2-equivalent), emissions are required to decline before 2015 and are further reduced to less than 50% of today’s emissions by 2050. For somewhat higher stabilization levels (e.g. below 590 ppmv CO2-equivalent) global emissions in the scenarios generally peak around 2010–2030, followed by a return to 2000 levels, on average around 2040. For high stabilization levels (e.g. below 710 ppmv CO2-equivalent) the median emissions peak around 2040 (high agreement, much evidence). Long-term stabilization scenarios highlight the importance of technology improvements, advanced technologies, learningby-doing, and induced technological change, both for achieving the stabilization targets and cost reduction (high agreement, much evidence). While the technology improvement and use of advanced technologies have been employed in scenarios largely exogenously in most of the literature, new literature covers learning-by-doing and endogenous technological change. The latter scenarios show different technology dynamics and ways in which technologies are deployed, while maintaining the key role of technology in achieving stabilization and cost reduction. Decarbonization trends are persistent in the majority of intervention and non-intervention scenarios (high agreement, much evidence). The medians of scenario sets indicate decarbonization rates of around 0.9 (pre-TAR) and 0.6 (post-TAR) compared to historical rates of about 0.3% per year. Improvements of carbon intensity of energy supply and the whole economic need to be much faster than in the past for the low stabilization levels. On the upper end of the range, decarbonization rates of up to 2.5% per year are observed in more stringent stabilization scenarios, where complete transition away from carbon-intensive fuels is considered. 172
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The scenarios that report quantitative results with drastic CO2 reduction targets of 60–80% in 2050 (compared to today’s emission levels) require increased rates of energy intensity and carbon intensity improvement by 2–3 times their historical levels. This is found to require different sets of mitigation options across regions, with varying shares of nuclear energy, carbon capture and storage (CCS), hydrogen, and biomass. The costs of stabilization crucially depend on the choice of the baseline, related technological change and resulting baseline emissions; stabilization target and level; and the portfolio of technologies considered (high agreement, much evidence). Additional factors include assumptions with regard to the use of flexible instruments and with respect to revenue recycling. Some literature identifies low-cost technology clusters that allow for endogenous technological learning with uncertainty. This suggests that a decarbonized economy may not cost any more than a carbon-intensive one, if technological learning is taken into account. There are different metrics for reporting costs of emission reductions, although most models report them in macroeconomic indicators, particularly GDP losses. For stabilization at 4–5 W/m2 (or ~ 590–710 ppmv CO2-equivalent) macroeconomic costs range from -1 to 2% of GDP below baseline in 2050. For a more stringent target of 3.5–4.0 W/m2 (~ 535–590 ppmv CO2-equivalent) the costs range from slightly negative to 4% GDP loss (high agreement, much evidence). GDP losses in the lowest stabilization scenarios in the literature (445-535 ppmv CO2-equivalent) are generally below 5.5% by 2050, however the number of studies are relatively limited and are developed from predominantly low baselines (high agreement, medium evidence). Multi-gas emission-reduction scenarios are able to meet climate targets at substantially lower costs compared to CO2-only strategies (for the same targets, high agreement, much evidence). Inclusion of non-CO2 gases provides a more diversified approach that offers greater flexibility in the timing of the reduction programme. Including land-use mitigation options as abatement strategies provides greater flexibility and cost-effectiveness for achieving stabilization (high agreement, medium evidence). Even if land activities are not considered as mitigation alternatives by policy, consideration of land (land-use and land cover) is crucial in climate stabilization for its significant atmospheric inputs and withdrawals (emissions, sequestration, and albedo). Recent stabilization studies indicate that land-use mitigation options could provide 15–40% of total cumulative abatement over the century. Agriculture and forestry mitigation options are projected to be cost-effective abatement strategies across the entire century. In some scenarios, increased commercial biomass energy (solid and liquid fuel) is a significant abatement strategy, providing 5–30% of cumulative abatement and potentially 1–15% of total primary energy over the century.
Chapter 3
Decision-making concerning the appropriate level of mitigation in a cost-benefit context is an iterative riskmanagement process that considers investment in mitigation and adaptation, co-benefits of undertaking climate change decisions and the damages due to climate change. It is intertwined with development decisions and pathways. Cost-benefit analysis tries to quantify climate change damages in monetary terms as the social cost of carbon (SCC) or time-discounted damages. Due to considerable uncertainties and difficulties in quantifying nonmarket damages, it is difficult to estimate SCC with confidence. Results depend on a large number of normative and empirical assumptions that are not known with any certainty. SCC estimates in the literature vary by three orders of magnitude. Often they are likely to be understated and will increase a few percent per year (i.e. 2.4% for carbon-only and 2–4% for the social costs of other greenhouse gases (IPCC, 2007b, Chapter 20). SCC estimates for 2030 range between 8 and 189 US$/ tCO2-equivalent (IPCC, 2007b, Chapter 20), which compares to carbon prices between 1 to 24 US$/tCO2-equivalent for mitigations scenarios stabilizing between 485-570 ppmv CO2equivalent) and 31 to 121 US$/tCO2-equivalent for scenarios stabilizing between 440-485 ppmv CO2-equivalent, respectively (high agreement, limited evidence). For any given stabilization pathway, a higher climate sensitivity raises the probability of exceeding temperature thresholds for key vulnerabilities (high agreement, much evidence). For example, policymakers may want to use the highest values of climate sensitivity (i.e. 4.5°C) within the ‘likely’ range of 2–4.5°C set out by IPCC (2007a, Chapter 10) to guide decisions, which would mean that achieving a target of 2°C (above the pre-industrial level), at equilibrium, is already outside the range of scenarios considered in this chapter, whilst a target of 3°C (above the pre-industrial level) would imply stringent mitigation scenarios, with emissions peaking within 10 years. Using the ‘best estimate’ assumption of climate sensitivity, the most stringent scenarios (stabilizing at 445–490 ppmv CO2-equivalent) could limit global mean temperature increases to 2–2.4°C above the pre-industrial level, at equilibrium, requiring emissions to peak before 2015 and to be around 50% of current levels by 2050. Scenarios stabilizing
Issues related to mitigation in the long-term context
at 535–590 ppmv CO2-equivalent could limit the increase to 2.8–3.2°C above the pre-industrial level and those at 590–710 CO2-equivalent to 3.2–4°C, requiring emissions to peak within the next 25 and 55 years, respectively (high agreement, medium evidence). Decisions to delay emission reductions seriously constrain opportunities to achieve low stabilization targets (e.g. stabilizing concentrations from 445–535 ppmv CO2-equivalent), and raise the risk of progressively more severe climate change impacts and key vulnerabilities occurring. The risk of climate feedbacks is generally not included in the above analysis. Feedbacks between the carbon cycle and climate change affect the required mitigation for a particular stabilization level of atmospheric CO2 concentration. These feedbacks are expected to increase the fraction of anthropogenic emissions that remains in the atmosphere as the climate system warms. Therefore, the emission reductions to meet a particular stabilization level reported in the mitigation studies assessed here might be underestimated. Short-term mitigation and adaptation decisions are related to long-term climate goals (high agreement, much evidence). A risk management or ‘hedging’ approach can assist policymakers to advance mitigation decisions in the absence of a long-term target and in the face of considerable uncertainties relating to the cost of mitigation, the efficacy of adaptation and the negative impacts of climate change. The extent and the timing of the desirable hedging strategy will depend on the stakes, the odds and societies’ attitudes to risks, for example with respect to risks of abrupt change in geo-physical systems and other key vulnerabilities. A variety of integrated assessment approaches exist to assess mitigation benefits in the context of policy decisions relating to such long-term climate goals. There will be ample opportunity for learning and mid-course corrections as new information becomes available. However, actions in the short term will largely determine what future climate change impacts can be avoided. Hence, analysis of short-term decisions should not be decoupled from analysis that considers long-term climate change outcomes (high agreement, much evidence).
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3.1 Emissions scenarios The evolution of future greenhouse gas emissions and their underlying driving forces is highly uncertain, as reflected in the wide range of future emissions pathways across (more than 750) emission scenarios in the literature. This chapter assesses this literature, focusing especially on new multi-gas baseline scenarios produced since the publication of the IPCC Special Report on Emissions Scenarios (SRES) (Nakicenovic et al., 2000) and on new multi-gas mitigation scenarios in the literature since the publication of the IPCC Third Assessment Report (TAR, Working Group III, Chapter 2, Morita et al., 2001). This literature is referred to as ‘post-SRES’ scenarios. The SRES scenarios were representative of some 500 emissions scenarios in the literature, grouped as A1, A2, B1 and B2, at the time of their publication in 2000. Of special relevance in this review is the question of how representative the SRES ranges of driving forces and emission levels are of the newer scenarios in the literature, and how representative the TAR stabilization levels and mitigation options are compared with the new multi-gas stabilization scenarios. Other important aspects of this review include methodological, data and other advances since the time the SRES scenarios were developed. This chapter uses the results of the Energy Modeling Forum (EMF-21) scenarios and the new Innovation Modelling Comparison Project (IMCP) network scenarios. In contrast to SRES and post-SRES scenarios, these new modellingcomparison activities are not based on fully harmonized baseline scenario assumptions, but rather on ‘modeller’s choice’ scenarios. Thus, further uncertainties have been introduced due to different assumptions and different modelling approaches. Another emerging complication is that even baseline (also called reference) scenarios include some explicit policies directed at emissions reduction, notably due to the Kyoto Protocol entering into force, and other climate-related policies that are being implemented in many parts of the world. Another difficulty in straightforward comparisons is that the information and documentation of the scenarios in the literature varies considerably. 3.1.1
The definition and purpose of scenarios
Scenarios describe possible future developments. They can be used in an exploratory manner or for a scientific assessment in order to understand the functioning of an investigated system (Carpenter et al., 2005). In the context of the IPCC assessments, scenarios are directed at exploring possible future emissions pathways, their main underlying driving forces and how these might be affected by policy interventions. The IPCC evaluation of emissions scenarios in 1994 identified four main purposes of emissions scenarios (Alcamo et al., 1995): 174
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• To provide input for evaluating climatic and environmental consequences of alternative future GHG emissions in the absence of specific measures to reduce such emissions or enhance GHG sinks. • To provide similar input for cases with specific alternative policy interventions to reduce GHG emissions and enhance sinks. • To provide input for assessing mitigation and adaptation possibilities, and their costs, in different regions and economic sectors. • To provide input to negotiations of possible agreements to reduce GHG emissions. Scenario definitions in the literature differ depending on the purpose of the scenarios and how they were developed. The SRES report (Nakicenovic et al., 2000) defines a scenario as a plausible description of how the future might develop, based on a coherent and internally consistent set of assumptions (‘scenario logic’) about the key relationships and driving forces (e.g. rate of technology change or prices). Some studies in the literature apply the term ‘scenario’ to ‘best-guess’ or forecast types of projections. Such studies do not aim primarily at exploring alternative futures, but rather at identifying ‘most likely’ outcomes. Probabilistic studies represent a different approach, in which the range of outcomes is based on a consistent estimate of the probability density function (PDF) for crucial input parameters. In these cases, outcomes are associated with an explicit estimate of likelihood, albeit one with a substantial subjective component. Examples include probabilistic projections for population (Lutz and Sanderson, 2001) and CO2 emissions (Webster et al., 2002, 2003; O’Neill, 2004). 3.1.1.1
Types of scenarios
The scenario literature can be split into two largely nonoverlapping streams – quantitative modelling and qualitative narratives (Morita et al., 2001). This dualism mirrors the twin challenges of providing systematic and replicable quantitative representation, on the one hand, and contrasting social visions and non-quantifiable descriptors, on the other (Raskin et al., 2005). It is particularly noteworthy that recent developments in scenario analysis are beginning to bridge this difficult gap (Nakicenovic et al., 2000; Morita et al., 2001; and Carpenter et al., 2005). 3.1.1.2
Narrative storylines and modelling
The literature based on narrative storylines that describe futures is rich going back to the first global studies of the 1970s (e.g. Kahn et al., 1976; Kahn and Weiner, 1967) and is also well represented in more recent literature (e.g. Peterson and Peterson, 1994; Gallopin et al., 1997; Raskin et al., 1998; Glenn and Gordon, 1997). Well known are the Shell scenarios that are principally based on narrative stories with illustrative quantification of salient driving forces and scenario outcomes (Wack, 1985a, 1985b; Schwartz, 1991; Shell, 2005).
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Issues related to mitigation in the long-term context
Catastrophic futures feature prominently in the narrative scenarios literature. They typically involve large-scale environmental or economic collapse, extrapolating current unfavourable conditions and trends in many regions.1 Many of these scenarios suggest that catastrophic developments may draw the world into a state of chaos within one or two decades. Greenhouse-gas emissions might be low in such scenarios because of low or negative economic growth, but seem unlikely to receive much attention in any case, in the light of more immediate problems. This report does not analyze such futures, except where cases provide emissions pathways. 3.1.1.3
Global futures scenarios
Global futures scenarios are deeply rooted in the long history of narrative scenarios (Carpenter et al., 2005; UNEP, 2002). The direct antecedents of contemporary scenarios lie with the future studies of the 1970s (Raskin et al., 2005). These responded to emerging concerns about the long-term sufficiency of natural resources to support expanding global populations and economies. This first wave of global scenarios included ambitious mathematical simulation models (Meadows et al., 1972; Mesarovic and Pestel, 1974) as well as speculative narrative (Kahn et al., 1976). At this time, scenario analysis was first used at Royal Dutch/Shell as a strategic management technique (Wack, 1985a, 1985b; Schwartz, 1991). A second round of integrated global analysis began in the late 1980s and 1990s, prompted by concerns with climate change and sustainable development. These included narratives of alternative futures ranging from ‘optimistic’ and ‘pessimistic’ worlds to consideration of ‘surprising’ futures (Burrows et al., 1991; the Central Planning Bureau of the Netherlands, 1992; Kaplan, 1994; Svedin and Aniansson, 1987; Toth et al., 1989). The long-term nature of the climate change issue introduced a new dimension and has resulted in a rich new literature of global emissions scenarios, starting from the IPCC IS92 scenarios (Pepper et al., 1992; Leggett et al., 1992) and most recent scenario comparisons projects (e.g. EMF and IMCP). The first decades of scenario assessment paved the way by showing the power – and limits – of both deterministic modelling and descriptive future analyses. A central challenge of global scenario exercises today is to unify these two aspects by blending the objectivity and clarity of quantification with the richness of narrative (Raskin et al., 2005). 3.1.2
Introduction to mitigation and stabilization scenarios
Climate change intervention, control, or mitigation scenarios capture measures and policies for reducing GHG emissions with respect to some baseline (or reference) scenario. They contain emission profiles, as well as costs associated with the emissions
1
reduction, but often do not quantify the benefits of reduced impacts from climate change. Stabilization scenarios are mitigation scenarios that aim at a pre-specified GHG reduction pathway, leading to stabilization of GHG concentrations in the atmosphere. For the purposes of this chapter, a scenario is identified as a mitigation or intervention scenario if it meets one of the following two conditions: • It incorporates specific climate change targets, which may include absolute or relative GHG limits, GHG concentration levels (e.g. CO2 or CO2-equivalent (CO2-eq) stabilization scenarios), or maximum allowable changes in temperature or sea level. • It includes explicit or implicit policies and/or measures of which the primary goal is to reduce CO2 or a broader range of GHG emissions (e.g. a carbon tax, carbon cap or a policy encouraging the use of renewable energy). Some scenarios in the literature are difficult to classify as mitigation (intervention) or baseline (reference or nonintervention), such as those developed to assess sustainable development (SD) paths. These studies consider futures that require radical policy and behavioural changes to achieve a transition to a postulated sustainable development pathway. Greenpeace formulated one of the first such scenarios (Lazarus et al., 1993). Many sustainable development scenarios are also included in this assessment. Where they do not include explicit policies, as in the case of SRES scenarios, they can be classified as baseline or non-intervention scenarios. For example, the SRES B1 family of reference scenarios can be characterized as having many elements of a sustainability transition that lead to generally low GHG emissions, even though the scenarios do not include policies or measures explicitly directed at emissions mitigation. Another type of mitigation (intervention or climate policy) scenario approach specifies future ‘worlds’ that are internally consistent with some specified climate target (e.g. a global temperature increase of no more than 1°C by 2100), and then works backwards to develop feasible emission trajectories and emission driver combinations leading to these targets. Such scenarios, also referred to as ‘safe landing’ or ‘tolerable window’ scenarios, imply the necessary development and implementation of climate policies intended to achieve these targets in the most efficient way (Morita et al., 2001). A number of such new multi-gas stabilization scenarios are assessed in this chapter. Confusion can arise when the inclusion of ‘non-climaterelated’ policies in a reference (non-intervention) scenario has the effect of significantly reducing GHG emissions. For example, energy efficiency or land-use policies that reduce
Prominent examples of such scenarios include the ‘Retrenchment’ (Kinsman, 1990), the ‘Dark Side of the Market World’ or ‘Change without Progress’ (Schwartz, 1991), the ‘Barbarization’ (Gallopin et al., 1997) and ‘A Passive Mean World’ (Glenn and Gordon, 1997).
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GHG emissions may be adopted for reasons that are not related to climate policies and may therefore be included in a non-intervention scenario. Such a scenario may include GHG emissions that are lower than some intervention scenarios. The root cause of this potential confusion is that, in practice, many policies can both reduce GHG emissions and achieve other goals (so-called multiple benefits). Whether such policies are assumed to be adopted for climate or non-climate policy-related reasons is determined by the scenario developer, based on the underlying scenario narrative. While this is a problem in terms of making a clear distinction between intervention and nonintervention scenarios, it is at the same time an opportunity. Because many decisions are not made for reasons of climate change alone, measures implemented for reasons other than climate change can have a significant impact on GHG emissions, opening up many new possibilities for mitigation (Morita et al., 2001). 3.1.3
Development trends and the lock-in effect of infrastructure choices
An important consideration in scenario generation is the nature of the economic development process and whether (and to what extent) developing countries will follow the development pathways of industrialized countries with respect to energy use and GHG emissions. The ‘lock-in’ effects of infrastructure, technology and product design choices made by industrialized countries in the post-World War II period of low energy prices are responsible for the major recent increase in world GHG emissions. A simple mimicking by developing countries of the development paradigm established by industrialized countries could lead to a very large increase in global GHG emissions (see Chapter 2). It may be noted, however, that energy/GDP elasticities in industrialized countries have first increased in successive stages of industrialization, with acceleration during the 1950s and 1960s, but have fallen sharply since then, due to factors such as relative growth of services in GDP share, technical progress induced by higher oil prices and energy conservation efforts. In developing countries, where a major part of the infrastructure necessary to meet development needs is still to be built, the spectrum of future options is considerably wider than in industrialized countries (e.g. on energy, see IEA, 2004). The spatial distribution of the population and economic activities is still not settled, opening the possibility of adopting industrial policies directed towards rural development and integrated urban, regional, and transportation planning, thereby avoiding urban sprawl and facilitating more efficient transportation and energy systems. The main issue is the magnitude and viability to tap the potential for technological ‘leapfrogging’, whereby developing countries can bypass emissionsintensive intermediate technology and jump straight to cleaner technologies. There are technical possibilities for less energyintensive development patterns in the long run, leading to low carbon futures in southern countries that are compatible with 176
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national objectives (see e.g. La Rovere and Americano, 2002). Section 12.2 of Chapter 12 develops this argument further. On the other hand, the barriers to such development pathways should not be underestimated, going from financial constraints to cultural behaviours in industrialized and developing countries, including the lack of appropriate institution building. One of the key findings of the reviewed literature is the longterm implications for GHG emissions of short- and mediumterm decisions concerning the building of new infrastructure, particularly in developing countries (see e.g. La Rovere and Americano, 2002; IEA, 2004). 3.1.4
Economic growth and convergence
Determinants of long-term GDP per person include labour force and its productivity projections. Labour force utilization depends on factors such as the number of working-age people, the level of structural unemployment and hours worked per worker. Demographic change is still the major determinant of the baseline labour supply (Martins and Nicoletti, 2005). Long-term projections of labour productivity primarily depend on improvements in labour quality (capacity building) and the pace of technical change associated with building up the capital-output ratio and the quality of capital. The literature examining production functions shows increasing returns because of an expanding stock of human capital and, as a result of specialization and investment in ‘knowledge’ capital (Meier, 2001; Aghion and Howitt, 1998), suggests that economic ‘catch-up’ and convergence strongly depend on the forces of ‘technological congruence’ and ‘social capability’ between the productivity leader and the followers (see the subsequent sub-section on institutional frameworks and Section 3.4 on the role of technological change). The economic convergence literature (Abramovitz, 1986; Baumol, 1986), using a standard neoclassical economic growth setup following Solow (1956), found evidence of convergence only between the richest countries. Other research efforts documented ‘conditional convergence’ – meaning that countries appeared to reach their own steady states at a fairly uniform rate of 2% per year (Barro, 1991; Mankiw et al., 1992). Jones (1997) found that the future steady-state distribution of per person income will be broadly similar to the 1990 distribution. Important differences would continue to arise among the bottom two-thirds of the income distribution, thus confirming past trends. Total factor productivity (TFP) levels and convergence for the evolution of income distribution are also important. Expected catch-up, and even overtaking per-person incomes, as well as changes in leaders in the world distribution of income, are among some of the findings in this literature. Quah (1993, 1996) found that the world is moving towards a bimodal income distribution. Some recent assessments demonstrate divergence, not convergence (World Bank, 2002; Halloy and Lockwood, 2005; UNSD, 2005).
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Issues related to mitigation in the long-term context
Convergence is limited for a number of reasons, such as imperfect mobility of factors (notably labour); different endowments (notably human capital); market segmentation (notably services); and limited technology diffusion. Social inertia (as referred to in Chapter 2, see Section 2.2.3) also contributes to delay convergence. Therefore only limited catchup can be factored in baseline scenarios: while capital quality is likely to push up productivity growth in most countries, especially in those lagging behind, labour quality is likely to drag down productivity growth in a number of countries, unless there are massive investments in education. However, appropriate policies may accelerate the adoption of new technologies and create incentives for human capital formation and thus accelerate convergence (Martins and Nicoletti, 2005). Nelson and Fagerberg, arguing within an evolutionary paradigm, have different perspectives on the convergence issue (Fagerberg, 1995; Fagerberg and Godinho, 2005; UNIDO, 2005). It should be acknowledged that the old theoretical controversy about steady-state economics and limits to growth still continues (Georgescu-Roegen, 1971). The above discussion provides the economic background for the range of assumptions on the long-term convergence of income between developing and developed countries (measured by GDP per person) found in the scenario literature. The annual rate of income convergence between 11 world regions in the SRES scenarios falls within the range of less than 0.5% in the A2 scenario family to less than 2% in A1 (both in PPP and MER metrics). The highest rate of income convergence in the SRES is similar to the observed convergence, during the period 1950–1990, of 90 regions in Europe (Barro and Sala-i-Martin 1997). However, Grübler et al. (2006) note that extending convergence analysis to national or sub-national level would suggest that income disparities are larger than suggested by simple inter-regional comparisons and that scenarios of (relative) income convergence are highly sensitive to the spatial level of aggregation used in the analysis. An important finding from the sensitivity analysis performed is that less convergence generally yields higher emissions (Grübler et al., 2004). In B2, an income ratio (between 11 world regions, in market exchange rates) of seven corresponds to CO2 emissions of 14.2 GtC in 2100, while shifting this income ratio to 16 would lead to CO2 emissions of 15.5 GtC in 2100. Results pointing in the same direction were also obtained for A2. This can be explained by slower TFP growth, slower capital turnover, and less ‘technological congruence’, leading to slower adoption of low-emission technologies in developing countries. On the other hand, as climate stabilization scenarios require global application of climate policies and convergence in the adoption of low-emission technologies, they are less compatible with low economic convergence scenarios. 3.1.5
Development pathways and GHG emissions
In the long run, the links between economic development and GHG emissions depend not only on the growth rate (measured
in aggregate terms), but also on the nature and structure of this growth. Comparative studies aiming to explain these differences help to determine the main factors that will ultimately influence the amount of GHG emissions, given an assumed overall rate of economic growth (Jung et al., 2000; see also examples discussed in Section 12.2 of Chapter 12). • Structural changes in the production system, namely the role of high or low energy-intensive industries and services. • Technological patterns in sectors such as energy, transportation, building, waste, agriculture and forestry – the treatment of technology in economic models has received considerable attention and triggered the most difficult debates within the scientific community working in this field (Edmonds and Clarke, 2005; Grubb et al., 2005; Shukla, 2005; Worrell, 2005; Köhler et al., 2006). • Geographical distribution of activities encompassing both human settlements and urban structures in a given territory, and its twofold impact on the evolution of land use, and on mobility needs and transportation requirements. • Consumption patterns – existing differences between countries are mainly due to inequalities in income distribution, but for a given income per person, parameters such as housing patterns, leisure styles, or the durability and rate of obsolescence of consumption goods will have a critical influence on long-run emission profiles. • Trade patterns – the degree of protectionism and the creation of regional blocks can influence access to the best available technologies, inter alia, and constraints on financial flows can limit the capacity of developing countries to build their infrastructure. These different relationships between development pathways and GHG emissions may (or may not) be captured in models used for long-term world scenarios, by changes in aggregated variables (e.g. per person income) or through more disaggregated economic parameters, such as the structure of expenses devoted to a given need (e.g. heating, transport or food, or the share of energy and transportation in the production function of industrial sectors). This means that alternative configurations of these underlying factors can be combined to give internally consistent socio-economic scenarios with identical rates of economic growth. It would be false to say that current economic models ignore these factors. They are to some extent captured by changes in economic parameters, such as the structure of household expenses devoted to heating, transportation or food; the share of each activity in the total household budget; and the share of energy and transportation costs in total costs in the industrial sector. These parameters remain important, but the outcome in terms of GHG emissions will also depend on dynamic links between technology, consumption patterns, transportation and urban infrastructure, urban planning, and rural-urban distribution of the population (see also Chapters 2 and 11 for more extensive discussions of some of these issues).
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3.1.6
Institutional frameworks
Recent research has included studies on the role of institutions as a critical component in an economy’s capacity to use resources optimally (Ostrom, 1990; Ostrom et al., 2002) and interventions that alter institutional structure are among the most accepted solutions in recent times for shaping economic structure and its associated energy use and emissions. Three important aspects of institutional structure are: 1. The extent of centralization and participation in decisions. 2. The extent (spanning from local to global) and nature of decision mechanisms. 3. Processes for effective interventions (e.g. the mix of market and regulatory processes). Institutional structures vary considerably across nations, even those with similar levels of economic development. Although no consensus exists on the desirability of a specific type of institutional framework, experience suggests that more participative processes help to build trust and social capital to better manage the environmental ‘commons’ (World Bank, 1992; Beierle and Cayford, 2002; Ostrom et al., 2002; Rydin, 2003). Other relevant developments may include greater use of market mechanisms and institutions to enhance global cooperation and more effectively manage global environmental issues (see also Chapter 12). A weak institutional structure basically explains why an economy can be in a position that is significantly below the theoretically efficient production frontier, with several economists terming it as a ‘missing link’ in the production function (Meier, 2001). Furthermore, weak institutions also cause frictions in economic exchange processes, resulting in high transaction costs. The existence of weak institutions in developing countries has implications for the capacity to adapt to or mitigate climate change. A review of the social capital literature and the implications for climate change mitigation policies concludes that successful implementation of GHG emission-reduction options will generally depend on additional measures to increase the potential market and the number of exchanges. This can involve strengthening the incentives for exchange (prices, capital markets, information efforts, etc.), introducing new actors (institutional and human capacity efforts), and reducing the risks of participating (legal framework, information, general policy context of market regulation). The measures all depend on the nature of the formal institutions, the social groups in society, and the interaction between them (see Chapter 2 and Halsnaes, 2002). Some of the climate change policy recommendations that are inspired by institutional economics include general capacity-building programmes, and local enterprise and finance development, for example in the form of soft loans, in addition to educational and training programmes (Halsnaes, 2002, see also Chapters 2 and 12). 178
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In today’s less industrialized regions, there is a large and relatively unskilled part of the population that is not yet involved in the formal economy. In many regions industrialization leads to wage differentials that draw these people into the more productive, formal economy, causing accelerated urbanization in the process. This is why labour force growth in these regions contributes significantly to GDP growth. The concerns relating to the informal economy are twofold: 1. Whether historical development patterns and relationships among key underlying variables will hold constant in the projections period. 2. Whether there are important feedbacks between the evolution of a particular sector and the overall development pattern that would affect GHG emissions (Shukla, 2005). Social and cultural processes shape institutions and the way in which they function. Social norms of ownership and distribution have a vital influence on the structure of production and consumption, as well as the quality and extent of the social ‘infrastructure’ sectors, such as education, which are paramount to capacity building and technological progress. Unlike institutions, social and culture processes are often more inflexible and difficult to influence. However, specific sectors, such as education, are amenable to interventions. Barring some negative features, such as segregation, there is no consensus as to the interventions that are necessary or desirable to alter social and cultural processes. On the other hand, understanding their role is crucial for assessing the evolution of the social infrastructure that underpins technological progress and human welfare (Jung et al., 2000) as well as evolving perceptions and social understanding of climate change risk (see Rayner and Malone, 1998; Douglas and Wildavsky, 1982; Slovic, 2000). While institutional arrangements are sometimes described as part of storylines, scenario specifications generally do not include explicit assumptions about them. The role of institutions in the implementation of development choices and its implications to climate change mitigation are discussed further in Section 12.2 of Chapter 12.
3.2 3.2.1
Baseline scenarios
Drivers of emissions
Trajectories of future emissions are determined by complex dynamic processes that are influenced by factors such as demographic and socio-economic development, as well as technological and institutional change. An often-used identity to describe changes in some of these factors is based on the IPAT identity (Impact = Population x Affluence x Technology – see Holdren, 2000; Ehrlich and Holdren, 1971) and in emissions modelling is often called the ‘Kaya identity’ (see Section 3.2.1.4 and Yamaji et al., 1991). These two relationships state that energy-related emissions are a function of population growth,
Chapter 3
Issues related to mitigation in the long-term context
3.2.1.1
Population projections
Current population projections reflect less global population growth than was expected at the time the TAR was published. Since the early 1990s demographers have revised their outlook on future population downward, based mainly on new data indicating that birth rates in many parts of the world have fallen sharply. Recent projections indicate a small downward revision to the medium (or ‘best guess’) outlook and to the high end of the uncertainty range, and a larger downward revision to the low end of the uncertainty range (Van Vuuren and O’Neill, 2006). This global result is driven primarily by changes in outlook for the Asia and the Africa-Latin America-Middle East (ALM) region. On a more detailed level, trends are driven by changes in the outlook for Sub-Saharan Africa, the Middle East and North Africa region, and the East Asia region, where recent data show lower than expected fertility rates, as well as a much more pessimistic view on the extent and duration of the HIV/AIDS crisis in Sub-Saharan Africa. In contrast, in the OECD region, updated projections are somewhat higher than previous estimates. This comes from changes in assumptions regarding migration (in the case of the UN projections), or to a more optimistic projection of future life expectancy (in the case of International Institute for Applied Systems Analysis (IIASA) projections). In the Eastern Europe and Central Asia (Reforming Economic, REF) region, projections have been revised downward, especially by the UN, driven mainly by recent data showing very low fertility levels and mortality rates that are quite high relative to other industrialized countries. Lutz et al. (2004), UN (2004) and Fisher et al. (2006) have produced updated projections for the world that extend to 2100. The most recent central projections for global population are
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GDP per person, changes in energy intensity, and carbon intensity of energy consumption. These factors are discussed in Section 3.2.1 to describe new information published on baseline scenarios since the TAR. There are more than 800 emission scenarios in the literature, including almost 400 baseline (nonintervention) scenarios. Many of these scenarios were collected during the IPCC SRES and TAR processes (Morita and Lee, 1998) and made available through the Internet. Systematic reviews of the baseline and mitigation scenarios were reported in the SRES (Nakicenovic et al., 2000) and the TAR (Morita et al., 2001), respectively. The corresponding databases have been updated and extended recently (Nakicenovic et al., 2006; Hanaoka et al., 2006).2 The recent scenario literature is discussed and compared with the earlier scenarios in this section.
2100
Figure 3.1: Comparison of population assumptions in post-SRES emissions scenarios with those used in previous scenarios. Blue shaded areas span the range of 84 population scenarios used in SRES or pre-SRES emissions scenarios; individual curves show population assumptions in 117 emissions scenarios in the literature since 2000. The two vertical bars on the right extend from the minimum to maximum of the distribution of scenarios by 2100. The horizontal bars indicate the 5th, 25th, 50th, 75th and the 95th percentiles of the distributions. Data source: After Nakicenovic et al., 2006.
1.4–2.0 billion (13–19%) lower than the medium population scenario of 10.4 billion used in the SRES B2 scenarios. As was the case with the outlook for 2050, the long-term changes at the global level are driven by the developing-country regions (Asia and ALM), with the changes particularly large in China, the Middle East and North Africa, and Sub-Saharan Africa. Most of the SRES scenarios still fall within the plausible range of population outcomes, according to more recent literature (see Figure 3.1). However, the high end of the SRES population range now falls above the range of recent projections from IIASA and the UN. This is a particular problem for population projections in East Asia, the Middle East, North Africa and the Former Soviet Union, where the differences are large enough to strain credibility (Van Vuuren and O’Neill, 2006). In addition, the population assumptions in SRES and the vast majority of more recent emissions scenarios do not cover the low end of the current range of population projections well. New scenario exercises will need to take the lower population projections into account. All other factors being equal, lower population projections are likely to result in lower emissions. However, a small number of recent studies that have used updated and lower population projections (Carpenter et al., 2005; Van Vuuren et al., 2007; Riahi et al., 2006) indicate that changes in other drivers of emissions might partly offset the impact of lower population assumptions, thus leading to no significant changes in emissions.
It should be noted that the sources of scenario data vary. For some scenarios the data comes directly from the modelling teams. In other cases it has been assembled from the literature or from other scenario comparison exercises such as EMF-19, EMF-21, and IMCP. For this assessment the scenario databases from Nakicenovic et al. (2006) and Hanaoka et al. (2006) were updated with the most recent information. The scenarios published before the year 2000 were retrieved from the database during SRES and TAR. The databases from Nakicenovic et al. (2006) and Hanaoka et al. (2006) can be accessed on the following websites: http://iiasa.ac.at/Research/TNT/WEB/scenario_database.html and www-cger.nies.go.jp/scenario.
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Economic activity is a dominant driver of energy demand and thus of greenhouse gas emissions. This activity is usually reported as gross domestic product (GDP), often measured in per-person (per-capita) terms. To derive meaningful comparisons over time, changes in price levels must be taken into account and corrected by reporting activities as constant prices taken from a base year. One way of reducing the effects of different base years employed across various studies is to report real growth rates for changes in economic output. Therefore, the focus below is on real growth rates rather than on absolute numbers.
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Given that countries and regions use particular currencies, another difficulty arises in aggregating and comparing economic output across countries and world regions. There are two main approaches: using an observed market exchange rate (MER) in a fixed year or using a purchasing power parity rate (PPP) (see Box 3.1). GDP trajectories in the large majority of long-term scenarios in the literature are calibrated in MER. A few dozen scenarios exist that use PPP exchange rates, but most of them are shorter-term, generally running until the year 2030. 3.2.1.3
GDP growth rates in the new literature
Many of the long-term economic projections in the literature have been specifically developed for climate-related scenario work. Figure 3.2 compares the global GDP range of 153 baseline scenarios from the pre-SRES and SRES literature with 130 new scenarios developed since SRES (post-SRES). There is a considerable overlap in the GDP numbers published, with a slight downward shift of the median in the new scenarios (by about 7%) compared to the median in the pre-SRES scenario literature. The data suggests no appreciable change in the distribution of GDP projections. A comparison of some recent shorter-term global GDP projections using the SRES scenarios is illustrated in Figure 3.3. The SRES scenarios project a very wide range of global economic per-person growth rates from 1% (A2) to 3.1% (A1) to 2030, both based on MER. This range is somewhat wider than that covered by the USDOE (2004) high and low scenarios (1.2–2.5%). The central projections of USDOE, IEA and the World Bank all contain growth rates of around 1.5–1.9%, thus occurring in the middle of the range of the SRES scenarios. Other medium-term energy scenarios are also reported to have growth rates in this range (IEA, 2004). Regionally, for the OECD, Eastern Europe and Central Asia (REF) regions, the correspondence between SRES outcomes and recent scenarios is relatively good, although the SRES GDP growth rates are somewhat conservative. In the ASIA region, the SRES range and its median value are just above that of recent studies. The differences between the SRES outcomes and more recent projections are largest in the ALM region (covering Africa, Latin America and the Middle East). Here, 180
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Figure 3.2: Comparison of GDP projections in post-SRES emissions scenarios with those used in previous scenarios. The median of the new scenarios is about 7% below the median of the pre-SRES and SRES scenario literature. The two vertical bars on the right extend from the minimum to maximum of the distribution of scenarios by 2100. The horizontal bars indicate the 5th, 25th, 50th, 75th and the 95th percentiles of the distributions.
the A1 and B1 scenarios clearly lie above the upper end of the range of current projections (4%–5%), while A2 and B2 fall near the centre of the range (1.4–1.7%). The recent short-term projections reported here contain an assumption that current barriers to economic growth in these regions will slow growth, at least until 2015. 3.2.1.4
The use of MER in economic and emissions scenarios modelling
The uses of MER-based economic projections in SRES have recently been criticized (Castles and Henderson, 2003a, 2003b; Henderson, 2005). The vast majority of scenarios published in the literature use MER-based economic projections. Some exceptions exist, for example, MESSAGE in SRES, and more recent scenarios using the MERGE model (Manne and Richels, 2003), along with shorter term scenarios to 2030, including the G-Cubed model (McKibbin et al., 2004a, 2004b), the International Energy Outlook (USDOE, 2004), the IEA World Energy Outlook (IEA, 2004) and the POLES model used by the European Commission (2003). The main criticism of the MER-based models is that GDP data for world regions are not corrected with respect to purchasing power parities (PPP) in most of the model runs. The implied consequence is that the economic activity levels in non-OECD countries generally appear to be lower than they actually are when measured in PPP units. In addition, the high growth SRES scenarios (A1 and B1 families) assume that regions tend to conditionally converge in terms of relative per-person income across regions (see Section 3.1.4). According to the critics, the use of MER, together with the assumption of conditional convergence, lead to overstated economic growth in the poorer regions and excessive growth in energy demand and emission levels.
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Figure 3.3: Comparison of global GDP growth per person in the SRES scenarios and more recent projections. Notes: SRES = (Nakicenovic et al., 2000), WB = World Bank (World Bank, 2004), DoE = assumptions used by US Department of Energy (USDOE, 2004), IEA assumptions used by IEA (IEA, 2002 and 2004); (Van Vuuren and O’Neill, 2006).
A team of SRES researchers responded to this criticism, indicating that the use of MER or PPP data does not in itself lead to different emission projections outside the range of the literature. In addition, they stated that the use of PPP data in most scenarios models was (and still is) infeasible, due to lack of required data in PPP terms, for example price elasticities and social accounting matrices (Nakicenovic et al., 2003; Grübler et al., 2004). A growing number of other researchers have also indicated different opinions on this issue or explored it in a more quantitative sense (e.g. Dixon and Rimmer, 2005; Nordhaus, 2006b; Manne and Richels, 2003; McKibbin et al., 2004a, 2004b; Holtsmark and Alfsen, 2004a, 2004b; Van Vuuren and Alfsen, 2006). There are at least three strands to this debate. The first is whether economic projections based on MER are appropriate, and thus whether the economic growth rates reported in the SRES and other MER-based scenarios are reasonable and robust. The second is whether the choice of the exchange rate matters when it comes to emission scenarios. The third is whether it is possible, or practical, to develop robust scenarios given the sparseness of relevant and required PPP data. While the GDP data are available in PPP, other economic scenario characteristics, such as capital and operational cost of energy facilities, are usually available either in domestic currencies or MER. Full model calibration in PPP for regional and global models is still difficult due to the lack of underlying data. This could be one of the reasons why a vast majority of long-term emissions scenarios continues to be calibrated in MER. On the question of whether PPP or MER should be employed in economic scenarios, the general recommendations are to use PPP where practical.3 This is certainly necessary when
3
comparisons of income levels across regions are of concern. On the other hand, models that analyse international trade and include trade as part of their economic projections, are better served by MER data given that trade takes place between countries in actual market prices. Thus, the choice of conversion factor depends on the type of analysis or comparison being undertaken. For principle and practical reasons, Nordhaus (2005) recommends that economic growth scenarios should be constructed by using regional or national accounting figures (including growth rates) for each region, but using PPP exchange rates for aggregating regions and updating over time by use of a superlative price index. In contrast, Timmer (2005) actually prefers the use of MER data in long-term modelling, as such data are more readily available, and many international relations within the model are based on MER. Others (e.g. Van Vuuren and Alfsen, 2006) also argue that the use of MER data in long-term modelling is often preferable, given that model parameters are usually estimated on MER data and international trade within the models is based on MER. The real economic consequences of the choice of conversion rates will obviously depend on how the scenarios are constructed, as well as on the type of model used for quantifying the scenarios. In some of the short-term scenarios (with a horizon to 2030) a bottom-up approach is taken where assumptions about productivity growth and investment/saving decisions are the main drivers of growth in the models (e.g. McKibbin et al., 2004a, 2004b). In longterm scenario models, a top-down approach is more commonly used where the actual growth rates are prescribed more directly, based on convergence or other assumptions about long-term growth potentials.
See, for example, UN (1993), (para 1.38): ‘When the objective is to compare the volumes of goods or services produced or consumed per head, data in national currencies must be converted into a common currency by means of purchasing power parities and not exchange rates. It is well known that, in general, neither market nor fixed exchange rates reflect the relative internal purchasing powers of different currencies. When exchange rates are used to convert GDP, or other statistics, into a common currency the prices at which goods and services in high-income countries are valued tend to be higher than in low-income countries, thus exaggerating the differences in real incomes between them. Exchange rate converted data must not, therefore, be interpreted as measures of the relative volumes of goods and services concerned.’
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Chapter 3
Box 3.1 Market Exchange Rates and Purchasing Power Parity To aggregate or compare economic output from various countries, GDP data must be converted into a common unit. This conversion can be based on observed market exchange (MER) rates or purchasing power parity (PPP) rates where, in the latter, a correction is made for differences in price levels between countries. The PPP approach is considered to be the better alternative if data is used for welfare or income comparisons across countries or regions. Market exchange rates usually undervalue the purchasing power of currencies in developing countries, see Figure 3.4. 1995US$/capita
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Figure 3.4: Regional GDP per person, expressed in MER and PPP on the basis of World Bank data aggregated to 17 global regions. Note: The left y-axis and columns compare absolute data, while the right y-axis and line graph compare the ratio between PPP and MER data. EECCA = countries of Eastern Europe, the Caucasus and Central Asia. Source: Van Vuuren and Alfsen, 2006.
Clearly, deriving PPP exchange rates requires analysis of a relatively large amount of data. Hence, methods have been devised to derive PPP rates for new years on the basis of price indices. Unfortunately, there is currently no single method or price index favoured for doing this, resulting in different sets of PPP rates (e.g. from the OECD, Eurostat, World Bank and Penn World Tables) although the differences tend to be small.
When it comes to emission projections, it is important to note that in a fully disaggregated (by country) multi-sector economic model of the global economy, aggregate index numbers play no role and the choice between PPP and MER conversion of income levels does not arise. However, in an aggregated model with consistent specifications (i.e. where model parameter estimation and model calibrations are all carried out based on consistent use of conversion factors), the effects of the choice of conversion measure on emissions should approximately cancel out. The reason can be illustrated by using the Kaya identity, which decomposes the emissions as follows: GHG = Population x GDP per person x Emissions per GDP or:
GHG = POP x
(
) (
GDP GHG x POP GDP
)
where GHG stands for greenhouse gas emissions, GDP 4
stands for economic output, and POP stands for population size.4 Given this relationship, emission scenarios can be represented, explicitly based on estimates of population development, economic growth, and development of emission intensity. Population is often projected to grow along a pre-described (exogenous) path, while economic activity and emission intensities are projected based on differing assumptions from scenario to scenario. The economic growth path can be based on historical growth rates, convergence assumptions, or on fundamental growth factors, such as saving and investment behaviour, productivity changes, etc. Similarly, future emission intensities can be projected based on historical experience,
Other components could be introduced in the identity, such as energy use, without changing the argument.
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In their modelling work, Manne and Richels (2003) and McKibbin et al. (2004a, 2004b) find some differences in emission levels between using PPP-based and MER-based estimates. Analysis of their work indicates that these results critically depend on, among other things, the combination of convergence assumptions and the mathematical approximation used between MER-GDP and PPP-GDP. In the Manne and Richels work for instance, autonomous efficiency improvement (AEI) is determined as a percentage of economic growth and estimated on the basis of MER data. In going from MER to PPP, the economic growth rate declines as expected, leading to a decline in the autonomous efficiency improvement. However, it is not clear whether it is realistic not to change the AEI rate when changing conversion measure. On the other hand, Holtsmark and Alfsen (2004a, 2004b), showed that in their simple model consistent replacement of the metric (PPP for MER) – for income levels as well as for underlying technology relationships – leads to a full cancellation of the impact of choice of metric on projected emission levels. To summarize: available evidence indicates that the differences between projected emissions using MER exchange rates and PPP exchange rates are small in comparison to the uncertainties represented by the range of scenarios and the likely impacts of other parameters and assumptions made in developing scenarios, for example, technological change. However, the debate clearly shows the need for modellers to be more transparent in explaining conversion factors, as well as taking care in determining exogenous factors used for their economic and emission scenarios. 3.2.1.5
Energy use
Future evolution of energy systems is a fundamental determinant of GHG emissions. In most models, energy demand growth is a function of key driving forces such as demographic change and the level and nature of human activities such as
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economic factors, such as labour productivity or other key factors determining structural changes in an economy, or technological development. The numerical expression of GDP clearly depends on conversion measures; thus GDP expressed in PPP will deviate from GDP expressed in MER, particularly for developing countries. However, when it comes to calculating emissions (or other physical measures such as energy), the Kaya identity shows that the choice between MER-based or PPPbased representations of GDP will not matter, since emission intensity will change (in a compensating manner) when the GDP numbers change. While using PPP values necessitates using lower economic growth rates for developing countries under the convergence assumption, it is also necessary to adjust the relationship between income and demand for energy with lower economic growth, leading to slower improvements in energy intensities. Thus, if a consistent set of metrics is employed, the choice of metric should not appreciably affect the final emission level.
2100
Figure 3.5: Comparison of 153 SRES and pre-SRES baseline energy scenarios in the literature compared with the 133 more recent, post-SRES scenarios. The ranges are comparable, with small changes on the lower and upper boundaries. Note: The two vertical bars on the right extend from the minimum to maximum of the distribution of scenarios by 2100. The horizontal bars indicate the 5th, 25th, 50th, 75th and the 95th percentiles of the distributions.
mobility, information processing, and industry. The type of energy consumed is also important. While Chapters 4 through 11 report on medium-term projections for different parts of the energy system, long-term energy projections are reported here. Figure 3.5 compares the range of the 153 SRES and preSRES scenarios with 133 new, post-SRES, long-term energy scenarios in the literature. The ranges are comparable, with small changes on the lower and upper boundaries, and a shift downwards with respect to the median development. In general, the energy growth observed in the newer scenarios does not deviate significantly from the previous ranges as reported in the SRES report. However, most of the scenarios reported here have not adapted the lower population levels discussed in Section 3.2.1.1. In general, this situation also exists for underlying trends as represented by changes in energy intensity, expressed as gigajoule (GJ)/GDP, and change in the carbon intensity of the energy system (CO2/GJ) as shown in Figure 3.6. In all scenarios, energy intensity improves significantly across the century – with a mean annual intensity improvement of 1%. The 90% range of the annual average intensity improvement is between 0.5% and 1.9% (which is fairly consistent with historic variation in this factor). Actually, this range implies a difference in total energy consumption in 2100 of more than 300% – indicating the importance of the uncertainty associated with this ratio. The carbon intensity is more constant in scenarios without climate policy. The mean annual long-term improvement rate over the course of the 21st century is 0.4%, while the uncertainty range is again relatively large (from -0.2 to 1.5%). At the high end of this range, some scenarios assume that energy technologies without CO2 emissions become competitive without climate policy as a result of increasing fossil fuel prices and rapid technology progress for carbon-free technologies. Scenarios with a low carbon-intensity improvement coincide with scenarios with a 183
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140
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Figure 3.6: Development of carbon intensity of energy (left) and primary energy intensity of GDP (right). Historical development and projections from SRES and pre-SRES scenarios compared to post-SRES scenarios. Note: The blue coloured range illustrates the range of 142 carbon intensity and 114 energy intensity – SRES and pre-SRES non-intervention scenarios. Source: After Nakicenovic et al., 2006.
large fossil fuel base, less resistance to coal consumption or lower technology development rates for fossil-free energy technologies. The long-term historical trend is one of declining carbon intensities. However, since 2000, carbon intensities are increasing slightly, primarily due to the increasing use of coal. Only a few scenarios assume the continuation of the present trend of increasing carbon intensities. One of the reasons for this may be that just a few of the recent scenarios include the effects of high oil prices. 3.2.1.6
Land-use change and land-use management
Understanding land-use and land-cover changes is crucial to understanding climate change. Even if land activities are not considered as subject to mitigation policy, the impact of landuse change on emissions, sequestration, and albedo plays an important role in radiative forcing and the carbon cycle. Over the past several centuries, human intervention has markedly changed land surface characteristics, in particular through large-scale land conversion for cultivation (Vitousek et al., 1997). Land-cover changes have an impact on atmospheric composition and climate via two mechanisms: biogeophysical and biogeochemical. Biogeophysical mechanisms include the effects of changes in surface roughness, transpiration, and albedo that, over the past millennium, are thought to have had a global cooling effect (Brovkin et al., 1999). Biogeochemical effects result from direct emissions of CO2 into the atmosphere from deforestation. Cumulative emissions from historical landcover conversion for the period 1920–1992 have been estimated to be between 206 and 333 Pg CO2 (McGuire et al., 2001), and as much as 572 Pg CO2 for the entire industrial period 1850–2000, roughly one-third of total anthropogenic carbon emissions over this period (Houghton, 2003). In addition, land management activities (e.g. cropland fertilization and water management, manure management and forest rotation lengths) also affect land-based emissions of CO2 and non-CO2 GHGs, 184
where agricultural land management activities are estimated to be responsible for the majority of global anthropogenic methane (CH4) and nitrous oxide (N2O) emissions. For example, USEPA (2006a) estimated that agricultural activities were responsible for approximately 52% and 84% of global anthropogenic CH4 or N2O emissions respectively in the year 2000, with a net contribution from non-CO2 GHGs of 14% of all anthropogenic greenhouse gas emissions in that year. Projected changes in land use were not explicitly represented in carbon cycle studies until recently. Previous studies into the effects of future land-use changes on the global carbon cycle employed trend extrapolations (Cramer et al., 2004), extreme assumptions about future land-use changes (House et al., 2002), or derived trends of land-use change from the SRES storylines (Levy et al., 2004). However, recent studies (e.g. Brovkin et al., 2006; Matthews et al., 2003; Gitz and Ciais, 2004) have shown that land use, as well as feedbacks in the society-biosphereatmosphere system (e.g. Strengers et al., 2004), must be considered in order to achieve realistic estimates of the future development of the carbon cycle; thereby providing further motivation for ongoing development to explicitly model land and land-use drivers in global integrated assessment and climate economic frameworks. For example, in a model comparison study of six climate models of intermediate complexity, Brovkin et al. (2006) concluded that land-use changes contributed to a decrease in global mean annual temperature in the range of 0.13–0.25°C, mainly during the 19th century and the first half of the 20th century, which is in line with conclusions from other studies, such as Matthews et al. (2003). In general, land-use drivers influence either the demand for land-based products and services (e.g. food, timber, bioenergy crops, and ecosystem services) or land-use production possibilities and opportunity costs (e.g. yield-improving technologies, temperature and precipitation changes, and CO2 fertilization). Non-market values – both use and non-use
Chapter 3
such as environmental services and species existence values respectively – will also shape land-use outcomes. Food demand is a dominant land-use driver, and population and economic growth are the most significant food demand drivers through per person consumption. Total world food consumption is expected to increase by over 50% by 2030 (Bruinsma, 2003). Moreover, economic growth is expected to generate significant structural change in consumption patterns, with diets shifting to include more livestock products and fewer staples such as roots and tubers. As a result, per person meat consumption is expected to show a strong global increase, in the order of 25% by 2030, with faster growth in developing and transitional countries of more than 40% and 30%, respectively (Bruinsma, 2003; Cassman et al., 2003). The Millennium Ecosystem Assessment (MEA) scenarios projected that global average meat consumption would increase from 36 kg/person in 1997 to 41–70 kg/person by 2050, with corresponding increases in overall food and livestock feed demands (Carpenter et al., 2005). Additional cropland is expected to be required to support these projected increases in demand. Beyond 2050, food demand is expected to level off with slow-down of population growth. Technological change is also a critical driver of land use, and a critical assumption in land-use projections. For example, Sands and Leimbach (2003) suggest that, globally, 800 million hectares of cropland expansion could be avoided with a 1% annual growth in crop yields. Similarly, Kurosawa (2006) estimates decreased cropland requirements of 18% by 2050, relative to 2000, with 2% annual growth in global average crop yields. Alternatively, the MEA scenarios implement a more complex representation of yield growth projections that, in addition to autonomous technological change, reflect the changes in production practices, investments, technology transfer, environmental degradation, and climate change. The net effect is positive, but shows declining productivity growth over time for some commodities, due in large part to diminishing marginal technical productivity gains and environmental degradation. In all these studies, increasing (decreasing) net productivity per hectare results in reduced (increased) cropland demand. Also important to land-use projections are potential changes in climate. For instance, rising temperatures and CO2 fertilization may improve regional crop yields in the short term, thereby reducing pressure for additional cropland and resulting in increased afforestation. However, modelling the beneficial impacts of CO2 fertilization is not as straightforward as once thought. Recent results suggest: lower crop productivity improvements in the field than shown previously with laboratory results (e.g. Ainsworth and Long, 2005); likely increases in tropospheric ozone and smog associated with higher temperatures that will depress plant growth and partially offset CO2 fertilization; expected increases in the variability of annual yields; CO2 effects favouring C3 plants (e.g. wheat, barley, potatoes, rice) over C4 plants (e.g. maize, sugar cane, sorghum, millet) while temperature increases favour C4 over
Issues related to mitigation in the long-term context
C3 plants; potential decreased nutritional content in plants subjected to CO2 fertilization and increased frequency of temperature extremes; and increases in forest disturbance frequency and intensity. See IPCC (2007b, Chapter 5) for an overall discussion of these issues and this literature. Long-term projections need to consider these issues, as well as examining the potential limitations or saturation points of plant responses. However, to date, long-term scenarios from integrated assessment models are only just beginning to represent climate feedbacks on terrestrial ecosystems, much less fully account for the many effects. Current integrated assessment representations only consider CO2 fertilization and changes in yearly average temperature, if they consider climate change effects at all (e.g. USCCSP, 2006; Van Vuuren et al., 2007). Only a few global studies have focused on long-term (century) land-use projections. The most comprehensive studies, in terms of sector and land-type coverage, are the SRES (Nakicenovic et al., 2000), the SRES implementation with the IMAGE model (Strengers et al., 2004), the scenarios from the Global Scenarios Group (Raskin et al., 2002), UNEP’s Global Environment Outlook (UNEP, 2002), the Millennium Ecosystem Assessment (Carpenter et al., 2005), and some of the EMF-21 Study models (Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006; Riahi et al., 2006; Van Vuuren et al., 2007). Recent sector-specific economic studies have also contributed global land-use projections for climate analysis, especially for forestry (Sands and Leimbach, 2003; Sohngen and Mendelsohn, 2003, 2007; Sathaye et al., 2006; Sohngen and Sedjo, 2006). In general, the post-SRES scenarios, though scarce in number for agricultural land use, have projected increasing global cropland areas, smaller forest-land areas, and mixed results for changes in global grassland (Figure 3.7). Unlike the SRES land-use scenarios that span a broader range while representing diverse storylines, the post-SRES scenarios, for forestry in particular, illustrate greater convergence across models on projected land-use change. Most post-SRES global scenarios project significant changes in agricultural land caused primarily by regional changes in food demand and production technology. Scenarios with larger amounts of land used for agriculture result from assumptions about higher population growth rates, higher food demands, and lower rates of technological improvement that generate negligible increases in crop yields. Combined, these effects are projected to lead to a sizeable expansion (up to 40%) of agricultural land between 1995 and 2100 (Figure 3.7). Conversely, lower population growth and food demand, and more rapid technological change, are projected to result in lower demand for agricultural land (as much as 20% less global agricultural acreage by the end of the century). In the short-term, almost all scenarios suggest an increase in cropland acreage and decline in forest land to meet projected increases in food, feed, and livestock grazing demands over the next few decades. Cropland changes range from -18% to +69% by 2050 relative to 2000 (from -123 to +1158 million hectares) 185
Issues related to mitigation in the long-term context
Chapter 3
(A) 1,6
and forest-land changes range from -18% to +3% (from -680 to +94 million hectares) by 2050. The changes in global forest generally mirror the agricultural scenarios; thereby, illustrating both the positive and negative aspects of some existing global land modelling. Most of the long-term scenarios assume that forest trends are driven almost exclusively by cropland expansion or contraction, and only deal superficially with driving forces, such as global trade in agricultural and forest products and conservation demands.
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Without incentives or technological innovation, biomass crops are currently not projected to assume a large share of global business as usual land cover – no more than about 4% by 2100. Until long-run energy price expectations rise (due to a carbon price, economic scarcity, or other force), biomass and other less economical energy supply technologies (some with higher greenhouse gas emission characteristics than biomass), are not expected to assume more significant baseline roles. 3.2.2
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Emissions
There is still a large span of CO2 emissions across baseline scenarios in the literature, with emissions in 2100 ranging from 10 GtCO2 to around 250 GtCO2. The wide range of future emissions is a result of the uncertainties in the main driving forces, such as population growth, economic development, and energy production, conversion, and end use, as described in the previous section. 3.2.2.1
CO2 emissions from energy and industry
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Figure 3.7: Global cropland (a), forest land (b) and grassland (c) projections. Notes: shaded areas indicate SRES scenario ranges, post-SRES scenarios denoted with solid lines. IMAGE-EMF21 = Van Vuuren et al. (2006a) scenario from EMF-21 Study; IMAGE-MA-xx = Millennium Ecosystem Assessment (Carpenter et al., 2005) scenarios from the IMAGE model for four storylines (GO = Global Orchestration, OS = Order from Strength, AM = Adapting Mosaic, TG = TechnoGarden); AgLU-x.x% = Sands and Leimbach (2003) scenarios with x.x% annual growth in crop yield; GTM-2003 = Sohngen and Mendelsohn (2003) global forest scenario; GTM-EMF21 = Sohngen and Sedjo (2006) global forest scenario from EMF-21 Study; GCOMAP-EMF21 = Sathaye et al. (2006) global forest scenario from EMF-21 Study; GRAPE-EMF21 = Kurosawa (2006) scenario from EMF-21 Study.
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This category of emissions encompasses CO2 emissions from burning fossil fuels, and industrial emissions from cement production and sometimes feedstocks.5 Figure 3.8 compares the range of the pre-SRES and SRES baseline scenarios with the post-SRES baseline scenarios. The figure shows that the scenario range has remained almost the same since the SRES. There seems to have been an upwards shift on the high and low end, but careful consideration of the data shows that this is caused by only very few scenarios and the change is therefore not significant. The median of the recent scenario distribution has shifted downwards slightly, from 75 GtCO2 by 2100 (pre-SRES and SRES) to about 60 GtCO2 (post SRES). The median of the recent literature therefore corresponds roughly to emissions levels of the intermediate SRES-B2 scenarios. The majority of scenarios, both pre-SRES and post-SRES, indicate an increase in emissions across most of the century, resulting in a range of 2100 emissions of 17–135 GtCO2 emissions from energy and industry (90th percentile of the full scenario distribution). Also the range of emissions depicted by the SRES scenarios is consistent with the range of other emission
5
It should be noted, however, that there are sometimes considerable ambiguities on what is actually included in emissions scenarios reported in the literature. Some of the CO2 emissions paths included in the ranges may therefore also include non-energy emissions such as those from land-use changes.
Chapter 3
Issues related to mitigation in the long-term context
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Figure 3.8: Comparison of the SRES and pre-SRES energy-related and industrial CO2 emissions scenarios in the literature with the post-SRES scenarios. Note: The two vertical bars on the right extend from the minimum to maximum of the distribution of scenarios and indicate the 5th, 25th, 50th, 75th and the 95th percentiles of the distributions by 2100. Source: After Nakicenovic et al., 2006
scenarios reported in the literature; both in the short and long term (see Van Vuuren and O’Neill, 2006). Several reasons may contribute to the fact that emissions have not declined in spite of somewhat lower projections for population and GDP. An important reason is that the lower demographic projections are only recently being integrated into emission scenario literature. Second, indirect impacts in the models are likely to offset part of the direct impacts. For instance, lower energy demand leads to lower fossil fuel depletion, thus allowing for a higher share of fossil fuels in the total energy mix over a longer period of time. Finally, in recent years there has been increasing attention to the interpretation of fossil fuel reserves reported in the literature. Some models may have decreased oil and gas use in this context, leading to higher coal use (and thus higher emissions).
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Analysis of scenario literature using the Kaya identity shows that pre-SRES and post-SRES baseline scenarios indicate a continuous decline of the primary energy intensity (EJ/GDP), while the change in carbon intensity (CO2/E) is much slower – or even stable (see Figure 3.6 and Section 3.2.1.5) in the post-SRES scenarios. In other words, in the absence of climate policy, structural change and energy efficiency improvement do contribute to lower emissions, but changes in the energy mix have a much smaller (or even zero) contribution. This conclusion is true for both the pre-SRES, SRES, as well as the post-SRES scenario literature. Baseline or reference emissions projections generally come from three types of studies: 1. Studies meant to represent a ‘best-guess’ of what might happen if present-day trends and behaviour continue. 2. Studies with multiple baseline scenarios under comprehensively different assumptions (storylines). 3. Studies based on a probabilistic approach. In literature, since the TAR, there has been some discussion of the purpose of these approaches (see Schneider, 2001; Grübler et al., 2002; Webster et al., 2002). Figure 3.9 (left panel) shows a comparison of the outcomes of some prominent examples of these approaches by comparing the outcome of baselines scenarios reported in the set of EMF-21 scenarios, representing the ‘best-guess’ approach, to the outcomes of the SRES scenarios, representing the storyline approach. In the right panel the SRES range is compared to the probabilistic approach (see Webster et al., 2002; Richels et al., 2004, for the probability studies). The figure shows that the range of different models participating in the EMF-21 study is somewhat smaller than those from SRES and the probabilistic approach. The range of EMF-21 scenarios result from different modelling approaches
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Figure 3.9: Comparison of various long-term scenario studies for CO2 emissions. Left panel: IPCC SRES, EMF-21 range (grey area), indicating the range of the lowest and highest reported values in the EMF-21 study (Weyant et al., 2006). Right panel: Webster et al. (2002) and Richels et al. (2004), indicating the mean (markers) and 95% intervals of the reported ranges of these studies (for the latter, showing the 95% interval of the combined range for optimistic and pessimistic technology).
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and from modeller’s insights into ‘the mostly likely values’ for driving forces. The two probabilistic studies and SRES explicitly assume more radical developments, but the number of studies involved is smaller. This leads to the low end of scenarios for the second category having very specific assumptions on development that may lead to low greenhouse gas emissions. The range of scenarios in the probabilistic studies tends to be between these extremes. Overall, the three different approaches seem to lead to consistent results, confirming the range of emissions reported in Figure 3.8 and confirming the emission range of scenarios used for the TAR. 3.2.2.2
Anthropogenic land emissions and sequestration
Some of the first global integrated assessment scenario analyses to account for land-use-related emissions were the IS92 scenario set (Leggett et al., 1992) and the SRES scenarios (Nakicenovic et al., 2000). However, out of the six SRES models, only four dealt with land use specifically (MiniCAM, MARIA, IMAGE 2.1, AIM), of which MiniCAM and MARIA used more simplified land-use modules. ASF and MESSAGE also simulated land-use emissions, however ASF did not have a specific land-use module and MESSAGE incorporated land-use results from the AIM model (Nakicenovic et al., 2000). Although SRES was a seminal contribution to scenario development, the treatment of land-use emissions was not the focus of this assessment; and, therefore, neither was the modelling of land-use drivers, land management alternatives, and the many emissions sources, sinks, and GHGs associated with land. While some recent assessments, such as UNEP’s Third Global Environment Outlook (UNEP, 2002) and the Millennium Ecosystem Assessment (Carpenter et al., 2005), have evaluated land-based environmental outcomes (global environment and ecosystem goods and services respectively), the Energy Modelling Forum’s 21st Study (EMF-21) was the first largescale exercise with a special focus on land as a climate issue. In EMF-21, the integrated assessment models incorporated non-CO2 greenhouse gases, such as those from agriculture, and carbon sequestration in managed terrestrial ecosystems (Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006). A few additional papers have subsequently improved upon their EMF-21 work (Riahi et al., 2006; Van Vuuren et al., 2007). In general, the land-use change carbon emissions scenarios since SRES project high global annual net releases of carbon in the near future that decline over time, leading to net sequestration by the end of the century in some scenarios (see Figure 3.10). The clustering of the non-harmonized post-SRES scenarios in Figure 3.10 suggests a degree of expert agreement that the decline in annual land-use change carbon emissions over time will be less dramatic (slower) than suggested by many of the SRES scenarios. Many of the post-SRES scenarios project a decrease in net deforestation pressure over time, as population growth slows and crop and livestock productivity increase; and, despite 188
Chapter 3
Gt CO2 8
SRES range
4 0 -4 -8 -12 2000
2020 MESSAGE-A2r GTM-2003 GTM-EMF21
2040
MESSAGE-EMF21 IMAGE2.3 GCOMAP-EMF21
2060 IMAGE-EMF21 AgLU-0.0%
2080 GRAPE-EMF21 AgLU-0.5%
2100 GTEM-EMF21 AgLU-1.0%
Figure 3.10: Baseline land-use change and forestry carbon net emissions. Notes: MESSAGE-EMF21 = Rao and Riahi (2006) scenario from EMF-21 Study; GTEM-EMF21 = Jakeman and Fisher (2006) scenario from EMF-21 Study; MESSAGE-A2r = Riahi et al. (2006) scenario with revised SRES-A2 baseline; IMAGE 2.3 = Van Vuuren et al. (2007) scenario; see Figure 3.7 notes for additional scenario references. The IMAGE 2.3 LUCF baseline scenario also emits non-CO2 emissions (CH4 and N2O) of 0.26, 0.30, 0.16 GtCO2-eq in 2030, 2050, and 2100, respectively.
continued projected loss of forest area in some scenarios (Figure 3.7), carbon uptake from afforestation and reforestation result in net sequestration. There also seems to be a consensus in recent non-CO2 GHG emission baseline scenarios that agricultural CH4 and N2O emissions will increase until the end of this century, potentially doubling in some baselines (see Table 3.1; Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006; Riahi et al., 2006; Van Vuuren et al., 2007). The modelling of agricultural emission sources varies across scenarios, with livestock and rice paddy methane and crop soil nitrous oxide emissions consistently represented. However, the handling of emissions from biomass burning and fossil fuel combustion are inconsistent across models; and cropland soil carbon fluxes are generally not reported, probably due to the fact that soil carbon sequestration mitigation options are not currently represented in these models. As noted in Section 3.2.1.6 climate change feedbacks could have a significant influence on long-term land use and, to date, are only partially represented in long-term modelling of land scenarios. Similarly, climate feedbacks can also affect landbased emissions. For instance, rising temperatures and CO2 fertilization can influence the amount of carbon that can be sequestered by land and may also lead to increased afforestation due to higher crop yields. Climate feedbacks in the carbon cycle could be extremely important. For instance, Leemans et al. (2002) showed that CO2 fertilization and soil respiration could be as important as the socio-economic drivers in determining the land-use emissions range. In addition, potentially important additional climate feedbacks in the carbon-climate system are currently not accounted
Chapter 3
Issues related to mitigation in the long-term context
Table 3.1: Baseline global agricultural non-CO2 greenhouse gas emissions from various long-term stabilization scenarios (GtCO2-eq). Non-CO2 GHG agricultural emissions sources represented*
Scenario
GtCO2-eq N2O
CH4 2000
2020
2050
2070
2100
2000
2020
2050
2070
2100
GTEM-EMF21
Enteric, manure, paddy rice, soil (N2O)
2.09
2.88
4.28
nm
nm
1.95
2.60
3.64
nm
nm
MESSAGEEMF21
Enteric, manure, paddy rice, soil (N2O)
2.58
3.42
6.05
6.00
5.06
2.57
3.48
4.65
3.79
2.32
IMAGE-EMF21
Enteric, manure, paddy rice, soil (N2O and CO2), biomass & agriculture waste burning, land clearing
3.07
4.15
4.34
4.37
4.55
2.02
2.75
3.11
3.23
3.27
GRAPE-EMF21
Enteric, manure, paddy rice, soil (N2O), biomass & agricultural waste burning
2.59
2.65
2.85
2.82
2.76
2.79
3.31
3.84
3.93
4.06
MESSAGE-A2r
Enteric, manure, paddy rice, soil (N2O)
2.58
3.43
4.78
5.52
6.57
2.57
3.48
4.37
4.77
5.22
IMAGE 2.3
Enteric, manure, paddy rice, soil (N2O and CO2), biomass & agricultural waste burning, land clearing
3.36
3.95
4.41
4.52
4.46
2.05
2.48
2.93
3.07
3.06
* CO2 emissions from fossil fuel combustion are tracked as well, but frequently reported (and mitigated) under other sector headings (e.g. energy, transportation). Notes: SAR GWPs used to compute carbon equivalent emissions. nm = not modelled. The GTEM-EMF21 scenario ran through 2050. See Figure 3.7 and 3.10 notes for the scenario references.
for in integrated assessment scenarios. Specifically, new insights suggest that soil drying and forest dieback may naturally reduce terrestrial carbon sequestration (Cox et al., 2000). However, these studies, as well as studies that try to capture changes in climate due to land-use change (Sitch et al., 2005) have thus far not been able to provide definitive guidance. A modelling system that fully couples land use change scenarios with a dynamic climate-carbon system is required in the future for such an assessment. 3.2.2.3
Non-CO2 greenhouse gas emissions
The emissions scenario chapter in the TAR (Morita et al., 2001) recommended that future research should include GHGs other than CO2 in new scenarios work. The reason was that, at that time, certainly regarding mitigation, most of the scenarios literature was still primarily focused on CO2 emissions from energy. Nevertheless, some multi-gas scenario work existed, including the SRES baseline scenarios, but also some other modelling efforts (Manne and Richels, 2001; Babiker et al., 2001; Tol, 1999). The most important non-CO2 gases include: methane (CH4), nitrous oxide (N2O), and a group of fluorinated compounds (F-gases, i.e., HFCs, PFCs, and SF6). Since the TAR, the number of modelling groups producing long-term emission scenarios for non-CO2 gases has dramatically increased. As a result, the quantity and quality of non-CO2 emissions scenarios has improved appreciably. Unlike CO2 where the main emissions-related sectors are 6
few (i.e. energy, industry, and land use), non-CO2 emissions originate from a larger and more diverse set of economic sectors. Table 3.2 provides a list of the major GHG emitting sectors and their corresponding emissions, estimated for 2000. Note that there is significant uncertainty concerning emissions from some sources of the non-CO2 gases, and the table summarizes the central values from Weyant et al. (2006) which has been used in long-term multi-gas scenario studies of the EMF-21. To make the non-CO2 emissions comparable to those of CO2, the common practice is to compare and aggregate emissions by using global warming potentials (GWPs). The most important work on non-CO2 GHG emissions scenarios has been done in the context of EMF-21 (De la Chesnaye and Weyant, 2006). The EMF-21 study updated the capability of long-term integrated assessment models for modelling non-CO2 GHG emissions. The results of the study are illustrated in Figure 3.11. Evaluating the long-term projections of anthropogenic methane emissions from the EMF-21 data shows a significant range in the estimates, but this range is consistent with that found in the SRES. The methane emission differences in the SRES are due to the different storylines. The differences in the EMF-21 reference cases are mainly due to changes in the economic activity level projected in key sectors by each of the models6. This could include, for example, increased agriculture production or increased supply of natural gas and below-ground coal in the energy sector. In addition, different modelling groups
In the EMF-21 study, reference case scenarios were considered to be ‘modeller’s choice’, where harmonization of input parameters and exogenous assumptions was not sought.
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Chapter 3
Table 3.2: Global Anthropogenic GHG Emissions for 2000 at sector level, as used in EMF-21 studies (MtCO2-eq/yr). Sector sub-total & percent of total ENERGY
LUCFa and AGRICULTURE
9,543 25% INDUSTRY
WASTE 1,448 4%
CH4
8,133 4,800
451 895
Petroleum syst. Stationary/Mobile sources
10,476
62 59
LUCF and agriculture (net) Soils
3,435
N2O
F-gases
224 2,607
Biomass Enteric fermentation Manure management Rice
491 1,745 224 649
Cement
1,434 4%
Notes:
CO2
Coal Natural gas 25,098 67%
Total all GHG
Sub-sectors
187 205 -
829
Adipic & nitric acid production HFC-23 PFCs SF6 Substitution of ODSb
158 95 106 55 191
Landfills
781
Wastewater Other
565 11
81 11
5,933
3,472
447
9%
1%
37,524
27,671
Gas as percent of total
74%
16%
a
LUCF is Land-use change and forestry. b HFCs are used as substitutes for ODSs in a range of applications Sources: Weyant et al, 2006.
employed various methods of representing methane emissions in their models and also made different assumptions about how specific methane emission factors for each economic sector change over time. Finally, the degree to which agricultural activities are represented in the models differs substantially. For example, some models represent all agricultural output as one large commodity, ‘agriculture’, while others have considerable disaggregation. Interestingly, the latter group of models tend to find slower emissions growth rates (see Van Vuuren et al., 2006b).
and magnesium production and processing), and the replacement of ozone-depleting substances (ODSs) with HFCs. Long-term projections of these fluorinated GHGs are generated by a fewer number of models, but still show a wide range in the results over the century. Total emissions of non-CO2 GHGs are projected to increase, but somewhat less rapidly than CO2 emissions, due to agricultural activities growing less than energy use.
The range of long-term projections of anthropogenic nitrous oxide emissions is wider than for methane in the EMF-21 data. Note that for N2O, base year emissions of the different models differ substantially. Two factors may contribute to this. First, different definitions exist as to what should be regarded as human-induced and natural emissions in the case of N2O emissions from soils. Second, some models do not include all emission sources.
Sulphur dioxide emission scenarios Sulphur emissions are relevant for climate change modelling as they contribute to the formation of aerosols, which affect precipitation patterns and, taken together, reduce radiative forcing. Sulphur emissions also contribute to regional and local air pollution. Global sulphur dioxide emissions have grown approximately in parallel with the increase in fossil fuel use (Smith et al., 2001, 2004; Stern, 2005). However, since around the late 1970s, the growth in emissions has slowed considerably (Grübler, 2002). Implementation of emissions controls, a shift to lower sulphur fuels in most industrialized countries, and the economic transition process in Eastern Europe and the Former Soviet Union have contributed to the lowering of global sulphur emissions (Smith et al., 2001). Conversely, with accelerated economic development, the growth of sulphur emissions in many parts of Asia has been high in recent decades, although growth rates have moderated recently (Streets et al., 2000;
The last group of non-CO2 gases are fluorinated compounds, which include hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulphur hexafluoride (SF6). The total global emissions of these gases are almost 450 MtCO2-eq, or slightly over 1% of all GHG for 2000. While the emissions of some fluorinated compounds are projected to decrease, many are expected to grow substantially because of the rapid growth rate of some emitting industries (e.g. semiconductor manufacture 190
3.2.2.4
Scenarios for air pollutants and other radiative substances
Chapter 3
140
Issues related to mitigation in the long-term context
Gt CO2-eq
CO 2
140
Gt CO2-eq EMF21 range
120
120
100
100
80
80
60
60
A1B
40
40
B2
20
20
A2
0 2000
50
2020
2040
2060
2080
2100
Gt CO2-eq
CH 4
50
40
40
30
30
20
20
10
10
0 2000
12
2020
2040
2060
2080
10
2060
2080
2100
EMF21 range
A2 B2 A1B B1 2020
2040
2060
2080
2100
8
6
6
4
4
2
2
2040
2060
2080
A2
A1B B2
0 2000
2100
6 Gt CO2-eq
EMF21 range
10
8
F-gases
6
5
5
4
4
2020
2040
B1
2060
2080
2100
Gt CO2-eq EMF21 range A2 A1B
3
3
2
2
1
1
0 2000
2040
12 Gt CO2-eq
N 2O
2020
2020
Gt CO2-eq
0 2000
2100
Gt CO2-eq
0 2000
B1
0 2000
2020
AIM EDGE GEMINI-E3 IMAGE MESSAGE POLES
2040
2060
AMIGA EPPA GRAPE IPAC MiniCAM SGM
2080
2100
0 2000
B2 B1 2020
2040
2060
2080
2100
COMBAT FUND GTEM MERGE PACE WIAGEM
Figure 3.11: Development of baseline emissions in the EMF-21 scenarios (left) and comparison between EMF21 and SRES scenarios (right). Source: De la Chesnaye and Weyant , 2006; see also Van Vuuren et al., 2006b
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Issues related to mitigation in the long-term context
Chapter 3
Stern, 2005; Cofala et al., 2006; Smith et al., 2004). A review of the recent literature indicates that there is some uncertainty concerning present global anthropogenic sulphur emissions, with estimates for the year 2000 ranging between 55.2 MtS (Stern, 2005), 57.5 MtS (Cofala et al., 2006) and 62 MtS (Smith et al., 2004).7
140
Many empirical studies have explored the relationship between sulphur emissions and related drivers, such as economic development (see for example, Smith et al., 2004). The main driving factors that have been identified are increasing income, changes in the energy mix, and a greater focus on air pollution abatement (as a consequence of increasing affluence). Together, these factors may result in an inverted U-shaped pattern of SO2 emissions, where emissions increase during early stages of industrialization, peak and then fall at higher levels of income, following a Kuznets curve (World Bank, 1992). This general trend is also apparent in most of the recent emissions scenarios in the literature.
60
MtS Smith et al. range
120
A2
100
A1 95% (SRES)
80 B1
Over time, new scenarios have generally produced lower SO2 emissions projections. A comprehensive comparison of the SRES and more recent sulphur-emission scenarios is given in Van Vuuren and O’Neill (2006). Figure 3.12 illustrates that the resulting spread of sulphur emissions over the medium term (up to the year 2050) is predominantly due to the varying assumptions about the timing of future emissions control, particularly in developing countries8. Scenarios at the lower boundary assume the rapid introduction of sulphur-control technologies on a global scale, and hence, a reversal of historical trends and declining emissions in the initial years of the scenario. Conversely, the upper boundaries of emissions are characterized by a rapid increase over coming decades, primarily driven by the increasing use of coal and oil at relatively low levels of sulphur control (SRES A1 and A2). The comparison shows that overall the SRES scenarios are fairly consistent with recent projections concerning the longterm uncertainty range (Smith et al., 2004; see Figure 3.12). However, the emissions peak over the short-term of some high emissions scenarios in SRES, which lie above the upper boundary estimates of the recent scenarios. There are two main reasons for this difference. First, recent sulphur inventories for the year 2000 have shifted downward. Second, and perhaps more importantly, new information on present and planned sulphur legislation in some developing countries, such as India (Carmichael et al., 2002) and China (Streets et al., 2001) has become available. Anticipating this change in legislation, recent scenarios project sulphur emissions to peak earlier and at lower levels compared to the SRES. Also the lower boundary projections of the recent literature have shifted downward slightly compared to the SRES scenario.
7 8
B2
40
Cofala et al.
median (SRES)
20
5% (SRES)
0 2000
2020
2040
2060
2080
2100
Figure 3.12: Sulphur dioxide emission scenarios. Notes: Thick coloured lines depict the four SRES marker scenarios and the black dashed lines show the median, 5th and 95th percentile of the frequency distribution for the full ensemble of all 40 SRES scenarios. The blue area (and the thin dashed lines in blue) illustrates individual scenarios and the range of Smith et al. (2004). Dotted lines indicate the minimum and maximum of sulphur emissions scenarios developed pre-SRES.
NOx emission scenarios The most important sources of NOx emissions are fossil fuel combustion and industrial processes, which combined with other sources such as natural and anthropogenic soil release, biomass burning, lightning, and atmospheric processes, amount to around 25 MtN per year. Considerable uncertainties exist, particularly around the natural sources (Prather et al., 1995; Olivier et al., 1998; Olivier and Berdowski, 2001; Cofala et al. (2006). Fossil fuel combustion in the electric power and transport sectors is the largest source of NOx, with emissions largely being related to the combustion practice. In recent years, emissions from fossil fuel use in North America and Europe are either constant or declining. Emissions have been increasing in most parts of Asia and other developing parts of the world, mainly due to the growing transport sector (Cofala et al., 2006; Smith, 2005; WBCSD, 2004). However in the longer term, most studies project that NOx emissions in developing countries will saturate and eventually decline, following the trend in the developed world. However, the pace of this trend is uncertain. Emissions are projected to peak in the developing world as early as 2015 (WBCSD, 2004, focusing on the transport sector) and, in worst cases, around the end of this century (see the high emissions projection of Smith, 2005). There have been very few global scenarios for NOx emissions since the earlier IS92 scenarios and the SRES. An important characteristic of these (baseline) scenarios is that they consider air pollution legislation (in the absence of any climate policy). Some scenarios, such as those by Bouwman and van Vuuren (1999) and Collins et al. (2000) often use IS92a as a ‘loose’ baseline, with new abatement policies added. Many scenarios
Note that the Cofala et al. (2006) inventory does not include emissions from biomass burning, international shipping and aircraft. In order to enhance comparability between the inventories, emissions from these sources (6 MtS globally) have been added to the original Cofala et al. (2006) values. The Amann (2002) projections were replaced by the recently updated IIASA-RAINS projection from Cofala et al. (2006).
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Issues related to mitigation in the long-term context
MtN Smith et al. range
95% (SRES)
120 A2
100 80
B2
60 A1
median (SRES)
40 B1
20
5% (SRES)
Cofala et al.
0 2000
2020
2040
2060
2080
2100
Figure 3.13: NOx emission scenarios. Notes: Thick coloured lines depict the four SRES marker scenarios and the black dashed lines show the median, 5th and 95th percentile of the frequency distribution for the full ensemble of all 40 SRES scenarios. The blue area illustrates the range of the recent Smith (2005) projections.
report rising NOx emissions up to the 2020s (Figure 3.13), with the lower boundary given by the short-term Cofala et al. (2006) reference scenario, projecting emissions to stay at about present levels for the next two to three decades. In the most recent longer-term scenarios (Smith, 2005), NOx emissions range between 32 MtN and 47 MtN by 2020, which corresponds to an increase in emissions of around 6–50% compared to 2000. The long-term spread is considerably larger, ranging from 9 MtN to 74 MtN by 2100 (see Figure 3.13). The majority of the SRES scenarios (70%) lie within the range of the new Smith (2005) scenarios. However, the upper and lower boundaries of the range of the recent projections have shifted downward compared to the SRES. Emission scenarios for black and organic carbon Black and organic carbon emissions (BC and OC) are mainly formed by incomplete combustion, as well as from gaseous precursors (Penner et al., 1993; Gray and Cass, 1998). The main sources of BC and OC emissions include fossil fuel combustion in industry, power generation, traffic and residential sectors, as well as biomass and agriculture waste burning. Natural sources, such as forest fires and savannah burning, are other major contributors. There has recently been some research suggesting that carbonaceous aerosols may contribute to global
warming (Hansen et al., 2000; Andrae, 2001; Jacobson, 2001; Ramaswamy et al., 2001). However, the uncertainty concerning the effects of BC and OC on the change in radiative forcing and hence global warming is still high (see Jacobson, 2001; and Penner et al., 2004). In the past, BC and OC emissions have been poorly represented in economic and systems engineering models due to unavailability of data. For example, in the IPCC’s Third Assessment Report, BC and OC estimates were developed by using CO emissions (IPCC, 2001b). One of the main reasons for this has been the lack of adequate global inventories for different emission sources. However, some detailed global and regional emission inventories of BC and OC have recently become available (Table 3.3). In addition, some detailed regional inventories are also available including Streets et al. (2003) and Kupiainen and Klimont (2004). While many of these are comprehensive with regard to detail, considerable uncertainty still exists in the inventories, mainly due to the variety in combustion techniques for different fuels as well as measurement techniques. In order to represent these uncertainties, some studies, such as Bond et al. (2004), provide high, low and ‘best-guess’ values. The development in the inventories has resulted in the possibility of estimating future BC and OC emissions. Streets et al. (2004) use the fuel-use information and technological change in the SRES scenarios to develop estimates of BC and OC emissions from both contained combustion as well as natural sources for all the SRES scenarios until 2050. Rao et al. (2005) and Smith and Wigley (2006) estimate BC and OC emissions until 2100 for two IPCC SRES scenarios, with an assumption of increasing affluence leading to an additional premium on local air quality. Liousse et al. (2005) use the fuel-mix and other detail in various energy scenarios and obtain corresponding BC and OC emissions. The inclusion of technological development is an important factor in estimating future BC and OC emissions because, even though absolute fossil fuel use may increase, a combination of economic growth, increased environmental consciousness, technology development and legislation could imply decreased pollutant emissions (Figure 3.14). Liousse et al. (2005) neglect the effects of technological change leading to much higher
Table 3.3: Emission inventories for black and organic carbon (Tg/yr). Source
Estimate year
Black carbon
Organic carbon
Penner et al., 1993
1980
13
-
Cooke and Wilson, 1996
1984
14a)
-
Cooke et al., 1999
1984
5-6.6a)
7-10a)
Bond et al., 2004
1996
4.7 (3-10)
8.9 (5-17)
12.3
81
5.7
9.5
Liousse et al.,1996 Junker and Liousse, 2006
1997
Note: a) Emissions from fossil-fuel use
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Issues related to mitigation in the long-term context
Chapter 3
Tg
Tg
50
28 40
24 20
30 16 12
20
8 10 4 0
0
2000
2020
2040
2060
2080
2100
2000
2020
2040
2060
Rao et al., 2005, A2
Rao et al., 2005, B1
Smith and Wigley,2006, B2
Streets et al., 2005,B1
Streets et al., 2005,A2
Streets et al., 2005, B2
Liousse et al., 2005, B1
Liousse et al., 2005, POLES
2080
2100
Figure 3.14: Total black carbon (left panel) and organic carbon (right panel) emission estimates in scenarios from different studies. Notes: Rao et al., (2005) include emissions from contained combustion only. Liousse et al. (2005), A2 not included as 2100 value of 100 Tg lies way above range.
emission estimates for BC emissions in the long-term in some cases, as compared to other studies such as Streets et al. (2004), Rao et al. (2005) and Smith and Wigley (2006), all of which show declining emissions in the long-term. Another important factor that Rao et al. (2005) also account for is current and proposed environmental legislation. This suggests the necessity for technology-rich frameworks that capture structural and technological change, as well as policy dynamics in the energy system in order to estimate future BC and OC emissions. Both Streets et al. (2004) and Rao et al. (2005) show a general decline in BC and OC emissions in developed countries, as well as in regions such as East Asia (including China). In other developing regions, such as Africa and South Asia, slower technology penetration rates lead to much lower emission reductions. There is a large decline in emissions from the residential sector in the developing countries, due to the gradual replacement of traditional fuels and technologies with more efficient ones. Transport-related emissions in both industrialized and developing countries decline in the long-term due to stringent regulations, technology improvements and fuel switching. To summarize, an important feature of the recent scenario literature is the long-term decline in BC/OC emission intensities per unit of energy use (or economic activity). The majority of the above studies thus indicate that the long-term BC and OC emissions might be decoupled from the trajectory of CO2 emissions.
3.3 3.3.1
3.3.2
Definition of a stabilization target
Mitigation scenarios explore the feasibility and costs of achieving specified climate change or emissions targets, often in comparison to a corresponding baseline scenario. The specified target itself is an important modelling and policy issue. Because Article 2 of United Nations Framework Convention on Climate Change (UNFCCC) states as its objective the ‘stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system’, most long-term mitigation studies have focused their efforts on GHG concentration stabilization scenarios. However, several other climate change targets may be chosen, for example the rate of temperature change, radiative forcing, or climate change impacts (see e.g. Richels et al., 2004; Van Vuuren et al., 2006b; Corfee-Morlot et al., 2005). In general, selecting a climate policy target early in the causeeffect chain of human activities to climate change impacts, such as emissions stabilization, increases the certainty of achieving required reduction measures, while increasing the uncertainty on climate change impacts (see Table 3.4). Selecting a climate target further down the cause-effect chain (e.g. temperature change, or even avoided climate impacts) provides for greater specification of a desired climate target, but decreases certainty of the emission reductions required to reach that target.
Mitigation scenarios
Introduction
This section contains a discussion of methodological issues (Sections 3.3.2–3.3.4), followed by a focus on the main 194
characteristics of different groups of mitigation scenarios, with specific attention paid to new literature on non-CO2 gases and land use (Sections 3.3.5.5 and 3.3.5.6). Finally, short-term scenarios with a regional or national focus are discussed in Section 3.3.6.
A commonly used target has been the stabilization of the atmospheric CO2 concentration. If more than one GHG is included, most studies use the corresponding target of stabilizing radiative forcing, thereby weighting the concentrations of the different gases by their radiative properties. The advantage of radiative forcing targets over temperature targets is that
Chapter 3
Issues related to mitigation in the long-term context
Table 3.4: Advantages and disadvantages of using different stabilization targets. Target
Advantages
Disadvantages
Mitigation costs
Lowest uncertainty on costs.
Very large uncertainty on global mean temperature increase and impacts. Very large uncertainty on global mean temperature increase and impacts. Either needs a different metric to allow for aggregating different gases (e.g. GWPs) or forfeits opportunity of substitution.
Emissions mitigation
Lower uncertainty on costs.
Does not allow for substitution among gases, thus losing the opportunity for multi-gas cost reductions. Indirect link to the objective of climate policy (e.g. impacts).
Concentrations of different greenhouse gases
Can be translated relatively easily into emission profiles (reducing uncertainty on costs).
Allows a wide range of CO2-only stabilization targets due to substitutability between CO2 and non-CO2 emissions.
Radiative forcing
Easy translation to emission targets, thus not including climate sensitivity in costs calculations. Does allow for full flexibility in substitution among gases. Connects well to earlier work on CO2 stabilization. Can be expressed in terms of CO2-eq concentration target, if preferred for communication with policymakers.
Indirect link to the objective of climate policy (e.g. impacts).
Global mean temperature
Metric is also used to organize impact literature; and as has shown to be a reasonable proxy for impacts
Large uncertainty on required emissions reduction as result of the uncertainty in climate sensitivity and thus costs.
Impacts
Direct link to objective of climate polices.
Very large uncertainties in required emission reductions and costs.
Based on: Van Vuuren et al., 2006b.
the consequences for emission trajectories do not depend on climate sensitivity, which adds an important uncertainty. The disadvantage is that a wide range of temperature impacts is possible for each radiative forcing level. By contrast, temperature targets provide a more direct first-order indicator of potential climate change impacts, but are less practical to implement in the real world, because of the uncertainty about the required emissions reductions. Another approach is to calculate risks or the probability of exceeding particular values of global annual mean temperature rise (see also Table 3.9). For example, Den Elzen and Meinshausen (2006) and Hare and Meinshausen (2006) used different probability density functions of climate sensitivity in the MAGICC simple climate model to estimate relationships between the probability of achieving climate targets and required emission reductions. Studies by Richels et al. (2004), Yohe et al. (2004), Den Elzen et al. (2006), Keppo et al. (2006), and Kypreos (2006) have used a similar probabilistic concept in an economic context. The studies analyze the relationship between potential mitigation costs and the increase in probability of meeting specific temperature targets. The choice of different targets is not only relevant because it leads to different uncertainty ranges, but also because it leads to different strategies. Stabilization of one type of target, such as temperature, does not imply stabilization of other possible targets, such as rising sea levels, radiative forcing, concentrations or emissions. For instance, a cost-effective way to stabilize
temperature is not radiative forcing stabilization, but rather to allow radiative forcing to peak at a certain concentration, and then decrease with additional emissions reductions so as to avoid (delayed) further warming and stabilize global mean temperature (see Meinshausen, 2006; Kheshgi et al., 2005; Den Elzen et al., 2006). Finally, targets can also be defined to limit a rate of change, such as the rate of temperature change. While such targets have the advantage of providing a link to impacts related to the rate of climate change, strategies to achieve them may be more sensitive to uncertainties and thus, require careful planning. The rate of temperature change targets, for instance, may be difficult to achieve in the short-term even, using multigas approaches (Manne and Richels, 2006; Van Vuuren et al., 2006a). 3.3.3
How to define substitution among gases
In multi-gas studies, a method is needed to compare different greenhouse gases with different atmospheric lifetimes and radiative properties. Ideally, the method would allow for substitution between gases in order to achieve mitigation cost reductions, although it may not be suitable to ensure equivalence in measuring climate impact. Fuglestvedt et al. (2003) provide a comprehensive overview of the different methods that have been proposed, along with their advantages and disadvantages. One of these methods, CO2-eq emissions based on Global Warming Potentials (GWP), has been adopted by current climate policies, such as the Kyoto Protocol and the US climate policy (White House, 2002). Despite the continuing scientific and economic 195
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Models using inter-temporal optimization (2) Models using GWPs as basis for substitution (9)
Figure 3.15: Reduction of emissions in the stabilization strategies aiming for stabilization at 4.5 W/m2 (multi-gas strategies) in EMF-21. Notes: Range for models using GWPs (blue; standard deviation) versus those not using them (purple; full range). For the first group, all nine reporting long-term models were used. For the second category, results of two of the three reporting models were used (the other model shows the same pattern with respect to the distribution among gases, but has a far higher overall reduction rate and, as such, an outlier). Data source: De la Chesnaye and Weyant, 2006.
debate on the use of GWPs (i.e. they are not based on economic considerations and use an arbitrary time horizon) the concept is in use under the UNFCCC, the Kyoto Protocol, and the US climate policy. In addition, no alternative measure has attained comparable status to date. Useful overviews of the mitigation and economic implication of substitution metrics are provided by Bradford (2001) and Godal (2003). Models that use inter-temporal optimization can avoid the use of substitution metrics (such as GWPs) by optimizing the reductions of all gases simultaneously under a chosen climate target. Inter-temporal optimization or perfect foresight models assume that economic agents know future prices and make decisions to minimize costs. Manne and Richels (2001) show, using their model, that using GWPs as the basis of substitution did not lead to the cost-optimal path (minimizing welfare losses) for the long-term targets analyzed. In particular, reducing methane early had no benefit for reaching the long-term target, given its short lifespan in the atmosphere. In the recent EMF-21 study some models validated this result (see De la Chesnaye and Weyant, 2006). Figure 3.15 shows the projected EMF-21 CO2, CH4, N2O, and F-gas reductions across models stabilizing radiative forcing at 4.5 W/m2. Most of the EMF-21 models based substitution between gases on GWPs. However, three models substituted gases on the basis of intertemporal optimization. While (for most of the gases) there are no systematic differences between the results from the two groups, for methane and some F-gases (not shown), there are clear differences related to the very different lifespans of these gases. The models that do not use GWPs, do not substantially reduce CH4 until the end of the time horizon. However, for models using GWPs, the reduction of CH4 emissions in the first three decades is substantial: here, CH4 reductions become a cost-effective short-term abatement strategy, despite the short lifespan (Van Vuuren et al., 2006b). It should be noted that if 196
a short-term climate target is selected (e.g. rate of temperature change) then inter-temporal optimization models would also favour early methane reductions. While GWPs do not necessarily lead to the most cost-effective stabilization solution (given a long-term target), they can still be a practical choice: in real-life policies an exchange metric is needed to facilitate emissions trading between gases within a specified time period. Allowing such exchanges creates the opportunity for cost savings through ‘what and where flexibility’. It is appropriate to ask what are the costs of using GWPs versus not using them and whether other ‘real world’ metrics exist that could perform better. O’Neill (2003) and Johansson et al. (2006) have argued that the disadvantages of GWPs are likely to be outweighed by the advantages, by showing that the cost difference between a multi-gas strategy and a CO2-only strategy is much larger than the difference between a GWPbased multi-gas strategy and a cost-optimal strategy. Aaheim et al. (2006) found that the cost of using GWPs compared to optimal weights, depends on the ambition of climate policies. Postponing the early CH4 reductions of the GWP-based strategy, as is suggested by inter-temporal optimization, generally leads to larger temperature increases during the 2000–2020 period. This is because the increased reduction of CO2 from the energy sector also leads to reduction of sulphur emissions (hence the cooling associated with sulphur-based aerosols) but allows the potential to be used later in the century. 3.3.4
Emission pathways
Emission pathway studies often focus on specific questions with respect to the consequences of timing (in terms of environmental impacts) or overall reduction rates needed for specific long-term targets, (e.g. the emission pathways developed by Wigley et al., 1996). A specific issue raised in the
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literature on emission pathways since the TAR has concerned a temporary overshoot of the target (concentration, forcing, or temperature). Meinshausen (2006) used a simple carbon-cycle model to illustrate that for low-concentration targets (i.e. below 3 W/m2/ 450 ppmv CO2-eq) overshoot is inevitable, given the feasible maximum rate of reduction. Wigley (2003) argued that overshoot profiles may give important economic benefits. In response, O’Neill and Oppenheimer (2004) showed that the associated incremental warming of large overshoots may significantly increase the risks of exceeding critical climate thresholds to which ecosystems are known to be able to adapt. Other emission pathways that lead to less extreme concentration overshoots may provide a sensible compromise between these two results. For instance, the ‘peaking strategies’ chosen by Den Elzen et al. (2006) show that it is possible to increase the likelihood of meeting the long-term temperature target or to reach targets with a similar likelihood at lower costs. Similar arguments for analyzing overshoot strategies are made by Harvey (2004), and Kheshgi et al. (2005). 3.3.5
Long-term stabilization scenarios
A large number of studies on climate stabilization have been published since the TAR. Several model comparison projects contributed to the new literature, including the Energy Modelling Forum’s EMF-19 (Weyant, 2004) and EMF-21 studies (De la Chesnaye and Weyant, 2006), that focused on technology change and multi-gas studies, respectively, the IMCP (International Model Comparison Project), which focused on technological change (Edenhofer et al., 2006), and the US Climate Change Science Programme (USCCSP, 2006). The updated emission scenario database (Hanaoka et al., 2006; Nakicenovic et al., 2006) includes a total of 151 new mitigation scenarios published since the SRES. Comparison of mitigation scenarios is more complicated now than at the time of the TAR because: • Parts of the modelling community have expanded their analysis to include non-CO2 gases, while others have continued to focus solely on CO2. As discussed in the previous section, multi-gas mitigation scenarios use different targets, thus making comparison more complicated. • Some recent studies have developed scenarios that do not stabilize radiative forcing (or temperature) – but show a peak before the end of the modelling time horizon (in most cases 2100). • At the time of the TAR, many studies used the SRES scenarios as baselines for their mitigation analyses, providing a comparable set of assumptions. Now, there is a broader range of underlying assumptions. This section introduces some metrics to group the CO2only and multi-gas scenarios so that they are reasonably comparable. In Figure 3.16 the reported CO2 concentrations in 2100 are plotted against the 2100 total radiative forcing (relative to pre-industrial times). Figure 3.16 shows that a
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Figure 3.16: Relationship of total radiative forcing vis-à-vis CO2 concentration for the year 2100 (25 multi-gas stabilization scenarios for alternative stabilization targets).
relationship exists between the two indicators. This can be explained by the fact that CO2 forms by far the most important contributor to radiative forcing – and subsequently, a reduction in radiative forcing needs to coincide with a reduction in CO2 concentration. The existing spread across the studies is caused by several factors, including differences in the abatement rate among alternative gases, differences in specific forcing values for GHGs and other radiative gases (particularly aerosols), and differences in the atmospheric chemistry and carbon cycle models that are used. Here, the relationship is used to classify the available mitigation literature into six categories that vary in the stringency of the climate targets. The most stringent group includes those scenarios that aim to stabilize radiative forcing below 3 W/m2. This group also includes all CO2-only scenarios that stabilize CO2 concentrations below 400 ppmv. In contrast, the least stringent group of mitigation scenarios have a radiative forcing in 2100 above 6 W/m2 – associated with CO2 concentrations above 660 ppmv. By far the most studied group of scenarios are those that aim to stabilize radiative forcing at 4–5 W/m2 or 485–570 ppmv CO2 (see Table 3.5). The classification of scenarios, as given in Table 3.5, permits the comparison of multi-gas and CO2-only stabilization scenarios according to groups of scenarios with comparable level of mitigation stringency. The studies have been classified on the basis of the reported targets, using the relationship from Figure 3.16 to permit comparability of studies using different stabilization metrics. The following section uses these categories (I to VI) to analyze the underlying dynamics of stabilization scenarios as a function of the stabilization target. However, it should be noted that the classification is subject to uncertainty and should thus to be used with care. 3.3.5.1
Emission reductions and timing
Figure 3.17 shows the projected CO2 emissions associated with the new mitigation scenarios. In addition, the figure depicts the range of the TAR stabilization scenarios (more than 80 197
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Table 3.5: Classification of recent (post-TAR) stabilization scenarios according to different stabilization targets and alternative stabilization metrics. Groups of stabilization targets were defined using the relationship in Figure 3.16.
Additional radiative forcing
CO2 concentration
W/m2
ppm
ppm
year
%
I
2.5-3.0
350-400
445-490
2000-2015
-85 to -50
6
II
3.0-3.5
400-440
490-535
2000-2020
-60 to -30
18
III
3.5-4.0
440-485
535-590
2010-2030
-30 to +5
21
IV
4.0-5.0
485-570
590-710
2020-2060
+10 to +60
118
V
5.0-6.0
570-660
710-855
2050-2080
+25 to +85
9
VI
6.0-7.5
660-790
855-1130
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+90 to +140
5
Category
CO2-eq Peaking year for Change in global emissions in 2050 concentration CO2 emissionsa (% of 2000 emissions)1
Total
No. of scenarios
177
Note: a Ranges correspond to the 15th to 85th percentile of the Post-TAR scenario distribution. Note that the classification needs to be used with care. Each category includes a range of studies going from the upper to the lower boundary. The classification of studies was done on the basis of the reported targets (thus including modeling uncertainties). In addition, also the relationship, which was used to relate different stabilization metrics, is subject to uncertainty (see Figure 3.16).
scenarios) (Morita et al., 2001). Independent of the stabilization level, scenarios show that the scale of the emissions reductions, relative to the reference scenario, increases over time. Higher stabilization targets do push back the timing of most reductions, even beyond 2100. An increasing body of literature assesses the attainability of very low targets of below 450 ppmv CO2 (e.g. Van Vuuren et al., 2007; Riahi et al., 2006). These scenarios from class I and II extend the lower boundary beyond the range of the TAR stabilization scenarios of 450 ppmv CO2 (see upper panels of Figure 3.17). The attainability of such low targets is shown to depend on: 1) using a wide range of different reduction options; and 2) the technology ‘readiness’ of advanced technologies, in particular the combination of bio-energy, carbon capture and geologic storage (BECCS). If biomass is grown sustainably, this combination may lead to negative emissions (Williams, 1998; Herzog et al., 2005), Rao and Riahi (2006), Azar et al. (2006) and Van Vuuren et al. (2007) all find that such negative emissions technologies might be essential for achieving very stringent targets. The emission range for the scenarios with low and intermediate targets between 3.5 and 5 W/m2 (scenarios in categories III and IV) are consistent with the range of the 450 and 550 ppmv CO2 scenarios in the TAR. Emissions in this category tend to show peak emissions around 2040 – with emissions in 2100 similar to, or slightly below, emissions today. Although for these categories less rapid and forceful reductions are required than for the more stringent targets, studies focusing on these stabilization categories find that a wide portfolio of reduction measures would be needed to achieve such emission pathways in a cost-effective way. The two highest categories of stabilization scenarios (V and VI) overlap with low-medium category baseline scenarios (see 9
Section 3.2). This partly explains the relatively small number of new studies on these categories. The emission profiles of these scenarios are found to be consistent with the emissions ranges as published in the TAR. There is a relatively strong relationship between the cumulative CO2 emissions in the 2000–2100 period and the stringency of climate targets (see Figure 3.18). The uncertainties associated with individual stabilization levels (shown by the different percentiles9) are primarily due to the ranges associated with individual stabilization categories, substitutability of CO2 and non-CO2-emissions, different model parameterizations of the carbon cycle, but they are also partly due to differences in emissions pathways (delayed reduction pathways can allow for somewhat higher cumulative emissions). In general, scenarios aiming for targets below 3 W/m2 require cumulative CO2 emissions of around 1100 GtCO2 (range of 800–1500 GtCO2). The cumulative emissions increase for subsequently less stringent targets. The middle category (4–5 W/m2) requires emissions to be in the order of 3000 GtCO2 (range of 2270–3920 GtCO2). The highest category (>6 W/m2) exhibits emissions, on average, around 5020 GtCO2 (range of 4400–6600 GtCO2). The timing of emission reductions also depends on the stringency of the stabilization target. Timing of climate policy has always been an important topic in the scenario literature. While some studies argue for early action for smooth transitions and stimulating technology development (e.g. Azar and Dowlatabadi, 1999, Van Vuuren and De Vries, 2001), others emphasize delayed response to benefit from better technology and higher CO2 fertilization rates from natural systems at later points in time (e.g. Wigley et al., 1996; Tol, 2000; for a more elaborate discussion on timing see also Section 3.6). This implies that a given stabilization target can be consistent with a range of interim targets. Nevertheless, stringent targets require an earlier peak of CO2 emissions (see Figure 3.19 and
Note that the percentiles are used to illustrate the statistical properties of the scenario distributions, and should not be interpreted as likelihoods in any probabilistic context.
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Figure 3.17: Emissions pathways of mitigation scenarios for alternative groups of stabilization targets (Categories I to VI, see Table 3.5). The pink area gives the projected CO2 emissions for the recent mitigation scenarios developed post-TAR. Green shaded areas depict the range of more than 80 TAR stabilization scenarios (Morita et al., 2001). Category I and II scenarios explore stabilization targets below the lowest target of the TAR. Source: After Nakicenovic et al., 2006, and Hanaoka et al., 2006
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Figure 3.18: Relationship between the scenario’s cumulative carbon dioxide emissions (2000–2100) and the stabilization target (stabilization categories I to VI, of Table 3.5). Data source: After Nakicenovic et al., 2006, and Hanaoka et al., 2006
Table 3.5). In the majority of the scenarios concerning the most stringent group (< 3 W/m2), emissions start to decline before 2015, and are further reduced to less than 50% of today’s emissions by 2050 (Table 3.5). The emissions profiles of these scenarios indicate the need for short-term infrastructure investments for a comparatively early decarbonization of the energy system. Achieving these low-emission trajectories requires a comprehensive global mitigation effort, including a further tightening of existing climate policies in Annex I countries, and simultaneous emission mitigation in developing countries, where most of the increase in emissions is expected in the coming decades. For the medium stringency group (4-5 W/m2) the peak of global emissions generally occurs around 2010 to 2030; followed by a return to 2000 levels, on average, around 2040 (with the majority of these scenarios returning 199
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to 2000 emissions levels between 2020 and 2060). For targets between 5–6 W/m2, the median emissions peak around 2070. The figure also indicates that the uncertainty range is relatively small for the more stringent targets, illustrating the reduced flexibility of the emissions path and the requirement for early mitigation. The less stringent categories allow more flexibility in timing. Most of the stringent stabilization scenarios of category I (and some II scenarios) assume a temporal overshoot of the stabilization target (GHG concentration, radiative forcing, or temperature change) before the eventual date of stabilization between 2100 and 2150. Recent studies indicate that while such ‘overshoot’ strategies might be inevitable for very low targets (given the climate system and socio-economic inertia), they might also provide important economic benefits. At the same time, however, studies note that the associated rate of warming from large overshoots might significantly increase the risk of exceeding critical climate thresholds. (For further discussion, see Section 3.3.4.) The right-hand panel of Figure 3.19 illustrates the time at which CO2 emissions will have to return to present levels. For stringent stabilization targets (below 4 W/m2; category I, II and III) emissions return to present levels, on average, before the middle of this century, that is about one to two decades after the year in which emissions peak. In most of the scenarios for the highest stabilization category (above 6 W/m2; category VI) emissions could stay above present levels throughout the century. The absolute level of the required emissions reduction does not only depend on the stabilization target, but also on the baseline emissions (see Hourcade and Shukla, 2001). This is clearly shown in the right-hand panel of Figure 3.20, which illustrates the relationship between the cumulative baseline emissions and the cumulative emissions reductions for the stabilization scenarios (by 2100). In general, scenarios with high baseline emissions require a higher reduction rate to reach the
same reduction target: this implies that the different reduction categories need to show up as diagonals in figure 3.20. This is indeed the case for the range of studies and the ‘category averages’ (large triangles). As indicated in the figure, a scenario with high baseline emissions requires much deeper emission reduction in order to reach a medium stabilization target (sometimes more than 3600 GtCO2) than a scenario with low baseline emissions to reach the most stringent targets (in some cases less than 1800 GtCO2). For the same target (e.g. category IV) reduction may differ from 370 to 5500 GtCO2. This comes from the large spread of emissions in the baseline scenarios. While scenarios for both stringent and less-stringent targets have been developed from low and high baseline scenarios, the data suggests that, on average, mitigation scenarios aimed at the most stringent targets start from the lowest baseline scenarios. In the short-term (2030), the relationship between emission reduction and baseline is less clear, given the flexibility in the timing of emission reductions (left-hand panel in Figure 3.20). While the averages of the various stabilization categories are aligned in a similar way to those discussed for 2100 (with exception of category I, for which the scenario sample is smaller than for the other categories); the uncertainty ranges here are very large. 3.3.5.2
GHG abatement measures
The abatement of GHG emissions can be achieved through a wide portfolio of measures in the energy, industry, agricultural and forest sectors (see also Edmonds et al., 2004b; Pacala and Socolow, 2004; Metz and Van Vuuren, 2006). Measures for reducing CO2 emissions range from structural changes in the energy system and replacement of carbon-intensive fossil fuels by cleaner alternatives (such as a switch from coal to natural gas, or the enhanced use of nuclear and renewable energy), to demand-side measures geared towards energy conservation and efficiency improvements. In addition, capturing carbon
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Figure 3.19: Relationship between the stringency of the stabilization target (category I to VI) and 1) the time at which CO2 emissions have to peak (left-hand panel), and 2) the year when emissions return to present (2000) levels. Data source: After Nakicenovic et al., 2006, and Hanaoka et al., 2006.
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Figure 3.20: Relationship between required cumulative emissions reduction and carbon emissions in the baseline by 2030 (left-hand panel) and 2100 (right-hand panel). Notes: Coloured rectangles denote individual scenarios for alternative stabilization targets (categories I to VI). The large triangles indicate the averages for each category. Data source: After Nakicenovic et al., 2006, and Hanaoka et al., 2006
during energy conversion processes with subsequent storage in geological formations (CCS) provides an approach for reducing emissions. Another important option for CO2 emission reduction encompasses the enhancement of forest sinks through afforestation, reforestation activities and avoided deforestation. In the energy sector the aforementioned options can be grouped into two principal measures for achieving CO2 reductions: 1. Improving the efficiency of energy use (or measures geared towards energy conservation). 2. Reducing the emissions per unit of energy consumption. The latter comprises the aggregated effect of structural changes in the energy systems and the application of CCS. A response index has been calculated (based on the full set of stabilization scenarios from the database) in order to explore the importance of these two strategies. This index is equal to the ratio of the reductions achieved through energy efficiency over those achieved by carbon-intensity improvements (Figure 3.21). Similar to Morita et al. (2001), it was discovered that the mitigation response to reduce CO2 emissions would shift over time, from initially focusing on energy efficiency reductions in the beginning of the 21st century to more carbonintensity reduction in the latter half of the century (Figure 3.21). The amount of reductions coming from carbon-intensity improvement is more important for the most stringent scenarios. The main reason is that, in the second half of the century, increasing costs of further energy efficiency improvements and decreasing costs of low-carbon or carbon-free energy sources make the latter category relatively more attractive. This trend is
also visible in the scenario results of model comparison studies (Weyant, 2004; Edenhofer et al., 2006). In addition to measures for reducing CO2 emissions from energy and industry, emission reductions can also be achieved from other gases and sources. Figure 3.22 illustrates the relative contribution of measures towards achieving climate stabilization from three main sources: 1. CO2 from energy and industry. 2. CO2 from land-use change. 3. The full basket of non-CO2 emissions from all relevant sources. The figure compares the contribution of these measures towards achieving stabilization for a wide range of targets (between 2.6 and 5.3 W/m2 by 2100) and baseline scenarios. An important conclusion across all stabilization levels and baseline scenarios is the central role of emissions reductions in the energy and industry sectors. All stabilization studies are consistent in that (independent of the baseline or target uncertainty) more than 65% of total emissions reduction would occur in this sector. The non-CO2 gases and land-use-related CO2 emissions (including forests) are seen to contribute together up to 35% of total emissions reductions.10 However, as noted further above, the majority of recent studies indicate the relative importance of the latter two sectors for the cost-effectiveness of integrated multi-gas GHG abatement strategies (see also Section 3.3.5.4 on CO2-only versus multi-gas mitigation and 3.3.5.5 on landuse). The strongest divergence across the scenarios concerns the contribution of land-use-related mitigation. The results range
10 Most of the models include an aggregated representation of the forest sector comprising the joint effects of deforestation, afforestation and avoided deforestation.
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Figure 3.21: Response index to assess priority setting in energy-intensity reduction (more than 1) or in carbon-intensity reduction (less than 1) for post-TAR stabilization scenarios. Note: The panels show the development of the index for the years 2020, 2050, and 2100 (66, 77, and 59 scenarios, respectively, for which data on energy, GDP and carbon emissions were available. Data source: After Nakicenovic et al., 2006, and Hanaoka et al., 2006)
from negative contributions of land-use change to potential emissions savings of more than 1100 GtCO2 over the course of the century (Figure 3.22). The primary reason for this is the considerable uncertainty with respect to future competition for land between dedicated bio-energy plantations and potential gains from carbon savings in terrestrial sinks. Some scenarios, for example, project massive expansion of dedicated bioenergy plantations, leading to an increase in emissions due to net deforestation (compared to the baseline). An illustrative example for the further breakdown of mitigation options is shown in Figure 3.23. The figure shows stabilization scenarios for a range of targets (about 3–4.5 W/ m2) based on four illustrative models (IMAGE, MESSAGE, AIM and IPAC) for which sufficient data were available. The scenarios share similar stabilization targets, but differ with respect to salient assumptions for technological change, longterm abatement potentials, as well as model methodology and structure. The scenarios are also based on different baseline scenarios. For example, cumulative baseline emissions over the course of the century range between 6000 GtCO2-eq in MESSAGE and IPAC scenarios to more than 7000 GtCO2-eq in the IMAGE and AIM scenarios. Figure 3.24 shows the primary energy mix of the baseline and the mitigation scenarios. It should be noted that the figure shows reduction on top of the baseline (e.g. other renewables may already make a large baseline contribution). Above all, Figure 3.23 illustrates the 202
importance of using a wide portfolio of reduction measures, with many categories of measures, showing contributions of more than a few hundred GtCO2 over the course of the century. In terms of the contribution of different options, there is agreement for some options, while there is disagreement for others. The category types that have a large potential over the long term (2000–2100) in at least one model include energy conservation, carbon capture and storage, renewables, nuclear and non-CO2 gases. These options could thus constitute an important part of the mitigation portfolio. However, the differences between the models also emphasize the impact of different assumptions and the associated uncertainty (e.g. for renewables, results can vary strongly depending on whether they are already used in the baseline, and how this category competes against other zero or low-emission options in the power sector, such as nuclear and CCS). The figure also illustrates that the limitations of the mitigation portfolio with respect to CCS or forest sinks (AIM and IPAC) would lead to relatively higher contributions of other options, in particular nuclear (IPAC) and renewables (AIM). Figure 3.23 also illustrates the increase in emissions reductions necessary to strengthen the target from 4.5 to about 3–3.6 W/m2. Most of the mitigation options increase their contribution significantly by up to a factor of more than two. This effect is particularly strong over the short term (2000–2030), indicating the need for early abatement in meeting stringent stabilization targets. Another important conclusion from the figure is that CCS and forest sink options are playing a relatively modest
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As noted above, assumptions with regards to the baseline can have significant implications for the contribution of individual mitigation options in achieving stabilization. Figure 3.24 clearly shows that the baseline assumptions of the four models differ, and that these differences play a role in explaining some of the results. For instance, the MESSAGE model already includes a large amount of renewables in its baseline and further expansion is relatively costly. Nevertheless, some common trends among the models may also be observed. First of all, almost all cases show a clear reduction in primary energy use. Second, in all models coal use is significantly reduced under the climate policy scenarios, compared to the baseline. It should be noted that in those models that consider CCS, the remaining fossil fuel use is mostly in combination with carbon capture and storage. In 2030, oil use is only modestly reduced by climate policies – this also applies to natural gas use. In 2100, both oil and gas are reduced compared to the baseline in most models. Finally, renewable energy and nuclear power increase in all models – although the distribution across these two options differs.
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Figure 3.22: Cumulative contribution of alternative mitigation measures by source (2000–2100) Note: Contributions for a wide range of stabilization targets (2.6–5.3 W/m2), indicated after the model name) and alternative baseline scenarios. Mitigation scenarios using the same baseline are indicated for each model as (a) and (b) reprectively. Data source: EMF-21, Smith and Wigley., 2006; Van Vuuren et al., 2007; Riahi et al., 2006
3.3.5.3 role in the short-term mitigation portfolio, particularly for the intermediate stabilization target (4.5 W/m2). The results thus indicate that the widespread deployment of these options might require relatively more time compared to the other options and
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models usually report the increase in energy system costs or the net present value (NPV) of the abatement costs. A common cost indicator is also the marginal cost/price of emissions reduction (US$/tC or US$/tCO2). Figure 3.25 shows the relationship between stabilization targets and alternative measures of mitigation costs, comprising GDP losses, net present value of abatement, and carbon price in terms of US$ /tCO2-eq. It is important to note that for the following reported cost estimates, the vast majority of the models assume transparent markets, no transaction costs, and thus perfect implementation of policy measures throughout the 21st century, leading to the universal adoption of cost-effective mitigation measures, such as carbon taxes or universal cap and trade programmes. These assumptions generally result in equal carbon prices across all regions and countries equivalent to global, least-cost estimates. Relaxation of these modelling assumptions, alone or in combination (e.g. mitigation-only in Annex I countries, no emissions trading, or CO2-only mitigation), will lead to an appreciable increase in all cost categories. The grey shaded area in Figure 3.25 illustrates the 10th– percentile of the mitigation cost ranges of recent studies, including the TAR. The area includes only those recent scenarios in the literature that report cost estimates based on a comprehensive mitigation analysis, defined as those that have a sufficiently wide portfolio of mitigation measures.11 The selection was made on a case-by-case basis for each scenario considered in this assessment. The Figure also shows results from selected illustrative studies (coloured lines). These studies report costs for a range of stabilization targets and are 90th
representative of the overall cost dynamics of the full set of scenarios. They show cases with high-, intermediate- and lowcost estimates (sometimes exceeding the 80th (i.e. 10th–90th) percentile range on the upper and lower boundaries of the greyshaded area). The colour coding is used to distinguish between individual mitigation studies that are based on similar baseline assumptions. Generally, mitigation costs (for comparable stabilization targets) are higher from baseline scenarios with relatively high baseline emissions (brown and red lines). By the same token, intermediate or low baseline assumptions result in relatively lower cost estimates (blue and green lines). Figure 3.25a shows that the majority of studies find that GDP losses increase with the stringency of the target, even though there is considerable uncertainty with respect to the range of losses. Barker et al. (2006) found that, after allowing for baseline emissions, the differences can be explained by: • The spread of assumptions in modelling-induced technical change. • The use of revenues from taxes and permit auctions. • The use of flexibility mechanisms (i.e. emissions trading, multi-gas mitigation, and banking). • The use of backstop technologies. • Allowing for climate policy related co-benefits. • Other specific modelling assumptions. Weyant (2000) lists similar factors but also includes the number and type of technologies covered, and the possible substitution between cost factors (elasticities). A limited set of studies finds negative GDP losses (economic gains) that arise from the assumption that a model’s baseline is assumed to be a non-optimal pathway and incorporates market imperfections. In these models, climate policies steer economies in the direction
11 The assessment of mitigation costs excludes stabilization scenarios that assume major limitation of the mitigation portfolio. For example, our assessment of costs does not include stabilization scenarios that exclude non-CO2 mitigation options for achieving multi-gas targets (for cost implications of CO2-only mitigation see also Section 3.3.5.4). The assessment nevertheless includes CO2 stabilization scenarios that focus on single-gas stabilization of CO2 concentrations. The relationship between the stabilization metrics given in Figure 3.16 is used to achieve comparability of multi-gas and CO2 stabilization scenarios.
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Figure 3.25: Figure 3.25 Relationship between the cost of mitigation and long-term stabilization targets (radiative forcing compared to pre-industrial level, W/m2 and CO2-eq concentrations). Notes: These panels show costs measured as a % loss of GDP (top), net present value of cumulative abatement costs (middle), and carbon price (bottom). The left-hand panels give costs for 2030, the middle panel for 2050, and the right-hand panel for 2100 repectively. Individual coloured lines denote selected studies with representative cost dynamics from very high to very low cost estimates. Scenarios from models sharing similar baseline assumptions are shown in the same colour. The grey-shaded range represents the 80th percentile of the TAR and post-TAR scenarios. NPV calculations are based on a discount rate of 5%. Solid lines show representative scenarios considering all radiatively active gases. CO2 stabilization scenarios are added based on the relationship between CO2 concentration and the radiative forcing targets shown in Figure 3.16. Dashed lines represent multi-gas scenarios, where the target is defined by the six Kyoto gases (other multi-gas scenarios consider all radiatively active gases). Data sources: CCSP scenarios (USCCSP, 2006); IMCP scenarios (Edenhofer et al., 2006); Post-SRES (PS) scenarios (Morita et al., 2001); Azar et al., 2006; Riahi et al., 2006; Van Vuuren et al., 2007.
of reducing these imperfections, for example by promoting more investment into research and development and thus achieving higher productivity, promoting higher employment rates, or removing distortionary taxes. The left-hand side panel of Figure 3.25a shows that for 2030, GDP losses in the vast majority of the studies (more than 90% of the scenarios) are generally below 1% for the target categories V and VI. Also in the majority of the category III and IV scenarios (70% of the scenarios) GDP losses are below 1%. However, it is important to note that for categories III and IV costs are higher, on average, and show a wider range than those for categories V
and VI. For instance, for category IV the interval lying between the 10th and 90th percentile varies from about 0.6% gain to about 1.2% loss. For category III, this range is shifted upwards (0.2–2.5%). This is also indicated by the median GDP losses by 2030, which increases from below 0.2% for categories V and VI, to about 0.2% for the category IV scenarios, and to about 0.6% for category III scenarios. GDP losses of the lowest stabilization categories (I & II) are generally below 3% by 2030, however the number of studies are relatively limited and in these scenarios stabilization is achieved predominantly from low baselines. The absolute GDP losses by 2030 correspond on average to a reduction of the annual GDP growth rate of less 205
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than 0.06 percentage points for the scenarios of category IV, and less than 0.1 and 0.12 percentage points for the categories III and I&II, respectively. GDP losses by 2050 (middle panel of Figure 3.25a) are comparatively higher than the estimates for 2030. For example, for category IV scenarios the range is between -1% and 2% GDP loss compared to baseline (median 0.5%), and for category III scenarios the range is from slightly negative to 4% (median 1.3%). The Stern review (2006), looking at the costs of stabilization in 2050 for a comparable category (500–550 CO2-eq) found a similar range of between -2% and +5%. For the studies that also explore different baselines (in addition to multiple stabilization levels), Figure 3.25a also shows that high emission baselines (e.g. high SRES-A1 or A2 baselines) tend to lead to higher costs. However, the uncertainty range across the models is at least of a similar magnitude. Generally, models that combine assumptions of very slow or incremental technological change with high baseline emissions (e.g. IGSM-CCSP) tend to show the relatively highest costs (Figure 3.25a). GDP losses of the lowest stabilization categories (I & II) are generally below 5.5% by 2050, however the number of studies are relatively limited and in these scenarios stabilization is achieved predominantly from low baselines. The absolute GDP losses numbers for 2050 reported above correspond on average to a reduction of the annual GDP growth rate of less than 0.05 percentage points for the scenarios of category IV, and less than 0.1 and 0.12 percentage points for the categories III and I&II, respectively. Finally, the most right-hand side panel of Figure 3.25a shows that GDP losses show a bigger spread and tend to be somewhat higher by 2100. GDP losses are between 0.3% and 3% for category V scenarios and -1.6% to about 5% for category IV scenarios. Highest costs are given by category III (from slightly negative costs up to 6.5%). The sample size for category I is not large enough for a statistical analysis. Similarly, for category II scenarios, the range is not shown as the stabilization scenarios of category II are predominantly based on low or intermediate baselines, and thus the resulting range would not be comparable to those from the other stabilization categories. However, individual studies indicate that costs become higher for more stringent targets (see, for example, studies highlighted in green and blue for the lowest stabilization categories in Figure 3.25a).12 The results for the net present value of cumulative abatement costs show a similar picture (Figure 3.25b). However, given the fact that abatement costs only capture direct costs, this cost estimate is by definition more certain.13 The interval from the 10th to the 90th percentile in 2100 ranges from nearly zero to about 11 trillion US$. The highest level corresponds to
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around 2–3% of the NPV of global GDP over the same period. Again, on the basis of comparison across models, it is clear that costs depend both on the stabilization level and baseline emissions. In general, the spread of costs for each stabilization category seems to be of a similar order to the differences across stabilization scenarios from different baselines. In 2030, the interval covering 80% of the NPV estimates runs from around 0–0.3 trillion for category IV scenarios. The majority of the more stringent (category III) scenarios range between 0.2 to about 1.6 trillion US$. In 2050, typical numbers for category IV are around 0.1–1.2 trillion US$ and, for category III, this is 1–5 trillion US$ (or below about 1% of the NPV of GDP). By 2100 the NPV estimates increase further, with the range up to 5 trillion for category IV scenarios and up to 11 trillion for category III scenarios, respectively. The results of these studies, published since the TAR, are consistent with the numbers presented in the TAR, although the new studies extend results to substantially lower stabilization levels. Finally, a similar trend is found for carbon price estimates. In 2030, typical carbon prices across the range of models and baselines for a 4.5 W/m2 stabilization target (category IV) range from around 1–24 US$/tCO2 (80% of estimates), with the median of about 11 US$/tCO2. For category III, the corresponding prices are somewhat higher and range from 18–79 US$/tCO2 (with the median of the scenarios around 45 US$/tCO2). Most individual studies for the most stringent category cluster around prices of about 100 US$/tCO2.14 Carbon prices by 2050 are comparatively higher than those in 2030. For example, costs of category IV scenarios by 2050 range between 5 and 65 US$/tCO2, and those for category III range between 30 and 155 US$/tCO2. Carbon prices in 2100 vary over a much wider range – mostly reflecting uncertainty in baseline emissions and technology development. For the medium target of 4.5 W/m2, typical carbon prices in 2100 range from 25–200 US$/tCO2 (80% of estimates). This is primarily a consequence of the nature of this metric, which often represents costs at the margin. Costs tend to slowly increase for more stringent targets – with a range between the 10th and 90th percentile of more than 35 to about 350 US$/tCO2 for category III. 3.3.5.4
The role of non-CO2 GHGs
As also illustrated by the scenario assessment in the previous sections, more and more attention has been paid since the TAR to incorporating non-CO2 gases into climate mitigation and stabilization analyses. As a result, there is now a body of literature (e.g. Van Vuuren et al., 2006b; De la Chesnaye and Weyant, 2006; De la Chesnaye et al., 2007) showing that mitigation costs for these sectors can be lower than for energy-
12 If not otherwise mentioned, the discussion of the cost ranges (Figure 3.25) refers to the 80th percentile of the TAR and post-TAR scenario distribution (see the grey area in Figure 3.25). 13 NPV calculations are based on carbon tax projections of the scenarios, using a discount rate of 5%, and assuming that the average cost of abatement would be half the marginal price of carbon. Some studies report abatement costs themselves, but for consistency this data was not used. The assumption of using half the marginal price of carbon results in a slight overestimation. 14 Note that the scenarios of the lowest stabilization categories (I and II) are mainly based on intermediate and low baseline scenarios.
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related CO2 sectors. As a result, when all these options are employed in a multi-gas mitigation policy, there is a significant potential for reduced costs, for a given climate policy objective, versus the same policy when CO2 is the only GHG directly mitigated. These cost savings can be especially important where carbon dioxide is not the dominant gas, on a percentage basis, for a particular economic sector and even for a particular region. While the previous sections have focused on the joint assessment of CO2 and multi-gas mitigation scenarios, this section explores the specific role of non-CO2 emitting sectors.15 A number of parallel numerical experiments have been carried out by the Energy Modelling Forum (EMF-21; De la Chesnaye and Weyant, 2006). The overall conclusion is that economic benefits of multi-gas strategies are robust across all models. This is even true, despite the fact that different methods were used in the study to compare the relative contribution of these gases in climate forcing (see Section 3.3.3). The EMF-21 study specifically focused on comparing stabilization scenarios aiming for 4.5 W/m2 compared to pre-industrial levels. There were two cases employed to achieve the mitigation target: 1. Directly mitigate CO2 emissions from the energy sector (with some indirect reduction in non-CO2 gases). 2. Mitigate all available GHG in costs-effective approaches using full ‘what’ flexibility.
Issues related to mitigation in the long-term context
Although the contributions of different gases change sharply over time, there is a considerable spread among the different models. Many models project relatively early reductions of both CH4 and the fluorinated gases under the multi-gas case. However, the subset of models that does not use GWPs as the substitution metric for the relative contributions of the different gases to the overall target, but does assume inter-temporal optimization in minimizing abatement costs, do not start to reduce CH4 emissions substantially until the end of the period. The increased flexibility of a multi-gas mitigation strategy is seen to have significant implications for the costs of stabilization across all models participating in the EMF-21. These scenarios concur that multi-gas mitigation is significantly cheaper than CO2-only. The potential reductions of the GHG price ranges in the majority of the studies between 30% and 85% (See Figure 3.27). Finally, the EMF-21 research also showed that, for some sources of non-CO2 gases, the identified reduction potential is still very limited (e.g. most agricultural sources for N2O emissions). For long-term scenarios (and more stringent targets) in particular, identifying how this potential may develop in time is a crucial research question. Attempts to estimate the maximum feasible reductions (and the development of potential over time) have been made in Van Vuuren et al. (2007). 3.3.5.5
In the CO2-only mitigation scenario, all models significantly reduced CO2 emissions, on average by about 75% in 2100 compared to baseline scenarios. Models still indicated some emission reductions for CH4 and N2O as a result of systemic changes in the energy system. Emissions of CH4 were reduced by about 20% and N2O by about 10% (Figure 3.26). In the multi-gas mitigation scenario, all models found that an appreciable percentage of the emission reductions occur through reductions of non-CO2 gases, which then results in smaller required reductions of CO2. The emission reduction for CO2 in 2100 therefore drops (on average) from 75% to 67%. This percentage is still rather high, caused by the large share of CO2 in total emissions (on average, 60% in 2100) and partly due to the exhaustion of reduction options for non-CO2 gases. The reductions of CH4 across the different models averages around 50%, with remaining emissions coming from sources for which no reduction options were identified, such as CH4 emissions from enteric fermentation. For N2O, the increased reduction in the multi-gas strategy is not as large as for CH4 (almost 40%). The main reason is that the identified potential for emission reductions for the main sources of N2O emissions, fertilizer use and animal manure, is still limited. Finally, for the fluorinated gases, high reduction rates (about 75%) are found across the different models.
Land use
Changes in land-use practices are regarded as an important component of long-term strategies to mitigate climate change. Modifications to land-use activities can reduce emissions of both CO2 and non-CO2 gases (CH4 and N2O), increase sequestration of atmospheric CO2 into plant biomass and soils, and produce biomass fuel substitutes for fossil fuels (see Chapters 4, 8, and 9 of this report for discussions of detailed land-related mitigation alternatives). Available information before the TAR suggested that land has the technical potential to sequester up to an additional 319 billion tonnes of CO2 (GtCO2) by 2050 in global forests alone (IPCC, 1996a; IPCC, 2000; IPCC, 2001a). In addition, current technologies are capable of substantially reducing CH4 and N2O emissions from agriculture (see Chapter 8). A number of global biomass energy potential assessments have also been conducted (see Berndes et al. 2003 for an overview).16 The explicit modelling of land-based climate change mitigation in long-term global scenarios is relatively new and rapidly developing. As a result, assessment of the long-term role of global land-based mitigation was not formally addressed by the Special Report on Land use, Land-use Change, and Forestry (IPCC, 2000) or the TAR. This section assesses the modelling of land in longterm climate stabilization and the relationship to detailed global forestry mitigation estimates from partial equilibrium sectoral models that model 100-year carbon price trajectories.
15 Note that the multi-gas stabilization scenarios, which consider only CO2 abatement options (discussed in this section), are not considered in the overall mitigation cost assessment of Section 3.3.5.3. 16 Most of the assessments are conducted with large regional spatial resolutions; exceptions are Fischer and Schrattenholzer (2001), Sørensen (1999), and Hoogwijk et al. (2005).
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0,0 2000
COMBAT GRAPE MESSAGE WIAGEM
EDGE GTEM MiniCAM
EPPA IMAGE PACE
Chapter 3
100
Issues related to mitigation in the long-term context
Carbon price of multi-gas scenarios as percent of carbon price of CO2-only scenarios 90th percentile
80 60
median
40 10th percentile
20 0 2025
2050
2075
2100
Figure 3.27: Reduction in GHG abatement price (%) in multi-gas stabilization scenarios compared to CO2-only cases. Ranges correspond to alternative scenarios for a stabilization target of 4.5 W/m2. Data source: De la Chesnaye and Weyant, 2006
Development of, among other things, global sectoral land mitigation models (e.g. Sohngen and Sedjo, 2006), bottomup agricultural mitigation costs for specific technologies (e.g. USEPA, 2006b), and biomass technical potential studies (e.g. Hoogwijk et al., 2005) has facilitated the formal incorporation of land mitigation in long-term integrated assessment of climate change stabilization strategies. Hoogwijk et al. (2005), for example, estimated the potential of abandoned agricultural lands for providing biomass for primary energy demand and identified the technical biomass supply limits of this land type (e.g. under the SRES A2 scenario, abandoned agricultural lands could provide for 20% of 2001 total energy demand). Sands and Leimbach (2003) conducted one of the first studies to explicitly explore land-based mitigation in stabilization, suggesting that the total cost of stabilization could be reduced by including land strategies in the set of eligible mitigation options (energy crops in this case). The Energy Modelling Forum Study-21 (EMF-21; De la Chesnaye and Weyant, 2006) was the first coordinated stabilization modelling effort to include an explicit evaluation of the relative role of land in stabilization; however, only a few models participated. Building on their EMF-21 efforts, some modelling teams have also generated even more recent stabilization scenarios with revised land modelling. These studies are conspicuously different in the specifics of their modelling of land and land-based mitigation (Rose et al., 2007). Differences in the types of land considered, emissions sources, and mitigation alternatives and implementation imply different opportunities and opportunity costs for land-related mitigation; and, therefore, different outcomes. Four of the modelling teams in the EMF-21 study directly explored the question of the cost-effectiveness of including land-based mitigation in stabilization solutions and found that
including these options (both non-CO2 and CO2) provided greater flexibility and was cost-effective for stabilizing radiative forcing at 4.5 W/m2 (Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006). Jakeman and Fisher (2006), for example, found that including land-use change and forestry mitigation options reduced the emissions reduction burden on all other emissions sources such that the projected decline in global real GDP associated with achieving stabilization was reduced to 2.3% at 2050 (3.4 trillion US$), versus losses of around 7.1% (10.6 trillion US$) and 3.3% (4.9 trillion US$) for the CO2-only and multi-gas scenarios, respectively.17 Unfortunately, none of the EMF-21 papers isolated the GDP effects associated with biomass fuel substitution or agricultural non-CO2 abatement. However, given agriculture’s small estimated share of total abatement (discussed below), the GDP savings associated with agricultural non-CO2 abatement could be expected to be modest overall, though potentially strategically significant to the dynamics of mitigation portfolios. Biomass, on the other hand, may have a substantial abatement role and therefore a large effect on the economic cost of stabilization. Notably, strategies for increasing cropland soil carbon have not been incorporated to date into this class of models (see Chapter 8 for an estimate of the short-term potential for enhancing agricultural soil carbon). Figure 3.28 presents the projected mitigation from forestry, agriculture, and biomass for the EMF-21 4.5 W/m2 stabilization scenarios, as well as additional scenarios produced by the MESSAGE and IMAGE models – an approximate 3 W/m2 scenario from Rao and Riahi (2006), a 4.5 W/m2 scenario from Riahi et al. (2006), and approximately 4.5, 3.7, and 2.9 W/m2 scenarios from Van Vuuren et al. (2007) (see Rose et al., 2007, for a synthesis). While there are clearly different land-based mitigation pathways being taken across models for the same stabilization target, and across targets with the same model and assumptions, some general observations can be made. First, forestry, agriculture, and biomass are called upon to provide significant cost-effective mitigation contributions (Rose et al., 2007). In the short-term (2000–2030), forest, agriculture, and biomass together could account for cumulative abatement of 10–65 GtCO2-eq, with 15–60% of the total abatement considered by the available studies, and forest/agricultural nonCO2 abatement providing at least three quarters of total land abatement.18 Over the entire century (2000–2100), cumulative land-based abatement of approximately 345–1260 GtCO2-eq is estimated to be cost-effective, accounting for 15–40% of total cumulative abatement. Forestry, agriculture, and biomass abatement levels are each projected to grow annually with relatively stable annual increases in agricultural mitigation and gradual deployment of biomass mitigation, which accelerates dramatically in the last half of the century to become the dominant land-mitigation strategy.
17 All values here are given in constant US dollars at 2000 prices. 18 The high percentage arises because some scenarios project that the required overall abatement from 2000–2030 is modest, and forestry and agricultural abatement options cost-effectively provide the majority of abatement.
209
Issues related to mitigation in the long-term context
0
Chapter 3
Agriculture
Gt CO2/yr
-1
-2
IMAGE 2.3 MESSAGE-EMF21 IMAGE 2.3 IMAGE 2.3 IMAGE-EMF21 GRAPE-EMF21 MESSAGE-EMF21 MESSAGE-A2r GTEM-EMF21
-3 2000
0
2020
2040
2060
2080
2100
Forest sequestration
Gt CO2/yr
However, there are substantial uncertainties. There is little agreement about the magnitudes of abatement (Figures 3.28 and 3.29). The scenarios disagree about the role of agricultural strategies targeting CH4 versus N2O, as well as the timing and annual growth of forestry abatement, with some scenarios suggesting substantial early deployment of forest abatement, while others suggest gradual annual growth or increasing annual growth.
-1 -2 -3 -4 -5
IMAGE2.3 MESSAGE-EMF21 IMAGE 2.3 IMAGE 2.3 IMAGE-EMF21 GRAPE-EMF21 MESSAGE-EMF21 MESSAGE-A2r GTEM-EMF21
-6 -7 -8 -9 -10 -11 2000
0
2020
2040
2060
2080
2100
2060
2080
2100
Biomass
Gt CO2/yr
-5
-10
-15 IMAGE 2.3 MESSAGE-EMF21 IMAGE 2.3 IMAGE 2.3 IMAGE-EMF21 GRAPE-EMF21 MESSAGE-EMF21 MESSAGE-A2r
-20
-25
-30 2000
2020
2040
Figure 3.28: Cost-effective agriculture, forest, and commercial biomass annual greenhouse gas emissions abatement from baselines from various 2100 stabilization scenarios (note y-axes have different ranges). Notes: The colour of the line indicates the 2100 stabilization target modelled: green < 3.25 W/m2 (< 420 CO2 concentration, < 510 CO2-eq concentration), pink 3.25–4 (42–490, 510–590), and dark blue 4–5 (490–570, 59–710). The IMAGEEMF21 and IMAGE 2.3 forest results are net of deforestation carbon losses induced by bio-energy crop extensification. These carbon losses are accounted for under forestry by the other scenarios. The MESSAGE-EMF21 results are taken from the sensitivity analysis of Rao and Riahi (2006). The GTEM-EMF21 scenarios ran through 2050 and the GTEM agriculture mitigation results include fossil fuel emissions reductions in agriculture (5-7% of the annual agricultural abatement). Scenario references: IMAGE-EMF21 (Van Vuuren et al., 2006a); MESSAGE-EMF21 (Rao and Riahi, 2006); MESSAGE-A2r (Riahi et al., 2006); GRAPE-EMF21 (Kurosawa, 2006); GTEM-EMF21 (Jakeman and Fisher, 2006); and IMAGE 2.3 (Van Vuuren et al., 2007). Source: Rose et al. (2007)
210
Figures 3.28 and 3.29 show that additional land-based abatement is expected to be cost-effective with tighter stabilization targets and/or higher baseline emissions (e.g. see the IMAGE 2.3 results for various stabilization targets and the MESSAGE 4.5 W/m2 stabilization results with B2 (EMF-21) and A2r baselines). Biomass is largely responsible for the additional abatement; however, agricultural and forestry abatement are also expected to increase. How they might increase is model and time dependent. In general, the overall mitigation role of agricultural abatement of rice methane, livestock methane, nitrous oxide (enteric and manure) and soil nitrous oxide is projected to be modest throughout the time horizon, with some suggestion of increased importance in early decades.
A number of the recent scenarios suggest that biomass energy alternatives could be essential for stabilization, especially as a mitigation strategy that combines the terrestrial sequestration mitigation benefits associated with bio-energy CO2 capture and storage (BECCS), where CO2 emissions are captured during biomass energy combustion for storage in geologic formations (e.g. Rao and Riahi, 2006; Riahi et al., 2006; Kurosawa, 2006; Van Vuuren et al., 2007; USCCSP, 2006). BECCS has also been suggested as a potential rapid-response prevention strategy for abrupt climate change. Across stabilization scenarios, absolute emissions reductions from biomass are projected to grow slowly in the first half of the century, and then rapidly in the second half, as new biomass processing and mitigation technologies become available. Figure 3.28 suggests biomass mitigation of up to 7 GtCO2/yr in 2050 and 27 GtCO2/yr in 2100, for cumulative abatement over the century of 115–749 GtCO2 (Figure 3.29). Figure 3.30 shows the amount of commercial biomass primary energy utilized in various stabilization scenarios. For example, in 2050, the additional biomass energy provides approximately 5–55 EJ for a 2100 stabilization target of 4–5 W/m2 and approximately 40–115 EJ for 3.25–4 W/m2, accounting for about 0–10 and 5– 20% of 2050 total primary energy respectively (USCCSP, 2006; Rose et al., 2007). Over the century, the additional bio-energy accounts for 500–6,700 EJ for targets of 4–5 W/m2 and 6100– 8000 EJ for targets of 3.25–4 W/m2 (1–9% and 9–13% of total primary energy, respectively). More biomass energy is supplied with tighter stabilization targets, but how much is required for any particular target depends on the confluence of the many different modelling assumptions. Modelled demands for biomass include electric power and end-use sectors (transportation, buildings, industry, and nonenergy uses). Current scenarios suggest that electric power is
Chapter 3
Issues related to mitigation in the long-term context
2000-2100
800 Gt CO2-eq
700 Agricultural CH4 Agricultural N2O
600
Forest 500
Biomass
400
300
200
100
0 IMAGE 2.3
MESSAGE
IMAGE 2.3
2.9 W/m2
~3.0 W/m2
3.7 W/m2
IMAGE 2.3
IMAGEEMF21
GRAPEEMF21 4.5 W/m2
MESSAGEEMF21
MESSAGEA2r
Figure 3.29: Cumulative cost-effective agricultural, forestry, and biomass abatement 2000–2100 from various 2100 stabilization scenarios. Source: Rose et al. (2007)
projected to dominate biomass demand in the initial decades and, in general, with less stringent stabilization targets. Later in the century (and for more stringent targets) transportation is projected to dominate biomass use. When biomass is combined with BECCS, biomass mitigation shifts to the power sector late in the century, to take advantage of the net negative emissions from the combined abatement option, such that BECCS could represent a signifant share of cumulative biomass abatement over the century (e.g. 30–50% of total biomass abatement from MESSAGE in Figure 3.29).
changes in global physical and economic forces. For example, Rao and Riahi (2006) offer intuitive results on the potential role of agricultural methane and nitrous oxide mitigation across industrialized and developing country groups, finding that agriculture is expected to form a larger share of the developing countries’ total mitigation portfolio; and, developing countries
200
EJ/yr
180 160
To date, detailed analyses of large-scale biomass conversion with CO2 capture and storage is scarce. As a result, current integrated assessment BECCS scenarios are based on a limited and uncertain understanding of the technology. In general, further research is necessary to characterize biomass’ long-term mitigation potential, especially in terms of land area and water requirements, constraints, and opportunity costs, infrastructure possibilities, cost estimates (collection, transportation, and processing), conversion and end-use technologies, and ecosystem externalities. In particular, present studies are relatively poor in representing land competition with food supply and timber production, which has a significant influence on the economic potential of bio-energy crops (an exception is Sands and Leimbach, 2003). Terrestrial mitigation projections are expected to be regionally unique, while still linked across time and space by
140 120 100 80 60
IMAGE 2.3 MESSAGE-EMF21 IMAGE 2.3 IGSM MINICAM IMAGE 2.3 IMAGE-EMF21 MESSAGE-EMF21 MESSAGE-A2r IGSM MINICAM IGSM MINICAM
40 20 0 2000
2020
2040
2060
2080
2100
Figure 3.30: Commercial biomass primary energy scenarios above baseline from various 2100 stabilization scenarios. Notes: The colour of the line indicates the 2100 stabilization target modelled: green < 3.25 W/m2 (< 420 CO2 concentration, < 510 CO2-eq concentration), pink 3.25–4 (420–490, 510–590), dark blue 4–5 (490–570, 590–710), and light blue 5–6 (570–660, 710–860). Scenario references: IMAGE-EMF21 (Van Vuuren et al., 2006a); MESSAGE-EMF21 (Rao and Riahi, 2006); MESSAGE-A2r (Riahi et al., 2006); IMAGE 2.3 (Van Vuuren et al., 2007); IGSM and MiniCAM (USCCSP, 2006). Source: Rose et al. (2007) ; USCCSP (2006)
211
Issues related to mitigation in the long-term context
are likely to provide the vast majority of global agricultural mitigation. Some aggregate regional forest mitigation results also are discussed below. However, given the paucity of published regional results from integrated assessment models, it is currently not possible to assess the regional land-use abatement potential in stabilization. Future research should direct attention to this issue in order to more fully characterize mitigation potential. In addition to the stabilization scenarios discussed thus far from integrated assessment and climate economic models, the literature includes long-term mitigation scenarios from global land sector economic models (e.g. Sohngen and Sedjo, 2006; Sathaye et al., 2006; Sands and Leimbach, 2003). Therefore, a comparison is prudent. The sectoral models use exogenous carbon price paths to simulate different climate policies and assumptions. It is possible to compare the stabilization and sectoral scenarios using these carbon price paths. Stabilization (e.g. EMF-21, discussed above) and ‘optimal’ (e.g. Sohngen and Mendelsohn, 2003) climate abatement policies suggest that carbon prices will rise over time.19 Table 3.6 compares the forest mitigation outcomes from stabilization and sectoral scenarios that have similar carbon price trajectories (Rose et al., 2007).20 Rising carbon prices will provide incentives for additional forest area, longer rotations, and more intensive management to increase carbon storage. Higher effective energy prices might also encourage shorter rotations for joint production of forest bioenergy feedstocks. Table 3.6 shows that the vast majority of forest mitigation is projected to occur in the second half of the century, with tropical regions in all but one scenario in Table 3.6 assuming a larger share of global forest sequestration/mitigation than temperate regions. The IMAGE results from EMF-21 are discussed separately below. Lower initial carbon prices shift early period mitigation to the temperate regions since, at that time, carbon incentives are inadequate for arresting deforestation. The sectoral models project that tropical forest mitigation activities are expected to be heavily dominated by land-use change activities (reduced deforestation and afforestation), while land management activities (increasing inputs, changing rotation length, adjusting age or species composition) are expected to be the slightly dominant strategies in temperate regions. The current stabilization scenarios model more limited and aggregated forestry GHG abatement technologies that do not distinguish the detailed responses seen in the sectoral models. The sectoral models, in particular, Sohngen and Sedjo (2006), suggest substantially more mitigation in the second half of the century compared to the stabilization scenarios. A number of factors are likely to be contributing to this deviation from the integrated assessment model results. First and foremost, is that Sohngen and Sedjo explicitly model future markets, which none of the integrated assessment models are currently
Chapter 3
capable of doing. Therefore, a low carbon price that is expected to increase rapidly results in a postponement of additional sequestration actions in Sohngen and Sedjo until the price (benefit) of sequestration is greater. Endogenously modelling forest biophysical and economic dynamics will be a significant future challenge for integrated assessment models. Conversely, the integrated assessment models may be producing a somewhat more muted forest sequestration response given: (i) Their explicit consideration of competing mitigation alternatives across all sectors and regions, and, in some cases, land-use alternatives. (ii) Their more limited set of forest-related abatement options, with all integrated assessment models modelling afforestation strategies, but only some considering avoided deforestation, and none modelling forest management options at this point. (iii) Some integrated assessment models (including those in Table 3.6) sequentially allocate land, satisfying population food and feed-demand growth requirements first. (iv) Climate feedbacks in integrated assessment models can lead to terrestrial carbon losses relative to the baseline. The IMAGE results in Table 3.6 provide a dramatic illustration of the potential implications and importance of some of these counterbalancing effects. Despite the planting of additional forest plantations in the IMAGE scenario, net tropical forest carbon stocks decline (relative to the baseline) due to deforestation induced by bioenergy crop extensification, as well as reduced CO2 fertilization that affects forest carbon uptake, especially in tropical forests, and decreases crop productivity, where the latter effect induces greater expansion of food crops onto fallow lands, thereby displacing stored carbon. In addition to reducing uncertainty about the maginitude and timing of land-based mitigation, biomass potential, and regional potential, there are a number of other important outcomes from changes in land that should be tracked and reported in order to properly evaluate long-term land mitigation. Of particular importance to climate stabilization are the albedo implications of land-use change, which can offset emissions reducing land-use change (Betts, 2000; Schaeffer et al., 2006), as well as the potential climate-driven changes in forest disturbance frequency and intensity that could affect the effectiveness of forest mitigation strategies. Non-climate implications should also be considered. As shown in the Millennium Ecosystem Assessment (Carpenter et al., 2005), land use has implications for social welfare (e.g. food security, clean water access), environmental services (water quality, soil retention), and economic welfare (output prices and production). A number of relevant key baseline land modelling challenges have already been discussed in Sections 3.2.1.6 and 3.2.2.2. Central to future long-term land mitigation modelling are
19 Optimal is defined in economic terms as the equating of the marginal benefits and costs of abatement. 20 Rose et al. (2007) report the carbon price paths from numerous stabilization and sectoral mitigation scenarios.
212
Chapter 3
Issues related to mitigation in the long-term context
Table 3.6: Cumulative forest carbon stock gains above baseline by 2020, 2050 and 2100, from long-term global forestry and stabilization scenarios (GtCO2).
US$2.73/tCO2 (in 2010) + 5% per year 2020
2050
2100
Sathaye et al., (2006)
World Temperate Tropics
na na na
91.3 25.3 55.1
353.8 118.8 242.0
Sohngen and Sedjo (2006) original baseline
World Temperate Tropics
0.0 3.3 -3.3
22.7 8.1 14.7
537.5 207.9 329.6
Sohngen and Sedjo (2006) accelerated deforestation baseline
World Temperate Tropics
1.5 1.1 0.7
15.0 12.1 2.9
487.3 212.7 275.0
Stabilization at 4.5 W/m2 (~650 CO2-eq ppmv) by 2100 2020
2050
2100
GRAPE-EMF21
World Temperate Tropics
-0.6 -0.2 -0.5
70.3 10.0 60.3
291.9 45.2 246.7
IMAGE-EMF21
World Temperate Tropics
-22.5 14.1 -36.6
-13.4 31.9 -45.3
10.4 78.3 -67.9
MESSAGE-EMF21*
World Temperate Tropics
0.0 0.0 0.0
3.5 0.1 3.4
152.5 23.4 129.1
Notes: * Results based on the 4.5 W/m2 MESSAGE scenario from the sensitivity analysis of Rao and Riahi (2006). Tropics: Central America, South America, Sub-Saharian Africa, South Asia, Southeast Asia. Temperate: North America, Western and Central Europe, Former Soviet Union, East Asia, Oceania, Japan. Na = data not available. Source: Stabilization data assembled from Rose et al. (2007)
improvements in the dynamic modelling of regional land use and land-use competition and mitigation cost estimates, as well as modelling of the implications of climate change for land-use and land mitigation opportunities. The total cost of any land-based mitigation strategy should include the opportunity costs of land, which are dynamic and regionally unique functions of changing regional biophysical and economic circumstances. In addition, the results presented in this section do not consider climate shifts that could dramatically alter land-use conditions, such as a permanent El-Nino-like state in tropical regions (Cox et al., 1999). To summarize, recent stabilization studies have found that land-use mitigation options (both non-CO2 and CO2) provide cost-effective abatement flexibility in achieving 2100 stabilization targets, in the order of 345–1260 GtCO2-eq (15–40%) of cumulative abatement over the century. In some scenarios, increased commercial biomass energy (solid and liquid fuel) is significant in stabilization, providing 115–749 GtCO2-eq (5–30%) of cumulative abatement and 500–9500 EJ of additional bio-energy above the baseline over the century (potentially 1–15% of total primary energy), especially as a net negative emissions strategy that combines biomass energy with CO2 capture and storage. Agriculture and forestry mitigation options are projected to be cost effective short-term and longterm abatement strategies. Global forestry models project greater additional forest sequestration than found in stabilization scenarios, a result attributable in part to differences in the modelling of forest dynamics and general economic feedbacks. Overall, the explicit modelling of land-based climate change
mitigation in long-term global scenarios is relatively immature, with significant opportunities for improving baseline and mitigation land-use scenarios. 3.3.5.6
Air pollutants, including co-benefits
Quantitative analysis on a global scale on the implications of climate mitigation for air pollutants such as SO2, NOx, CO, VOC (volatile organic compounds), BC (black carbon) and OC (organic carbon), are relatively scarce. Air pollutants and greenhouse gases are often emitted by the same sources, and changes in the activity of these sources affect both types of emissions. Previous studies have focused on purely ancillary benefits to air pollution that accrue from a climate mitigation objective, but recently there is a focus on integrating air quality and climate concerns, thus analyzing the co-benefits of such policies. Several recent reviews have summarized the issues related to such benefits (OECD 2000, 2003). They cover absolute air pollutant emission reductions, monetary value of reduced pollution, the climatic impacts of such reductions and the improved health effects due to reduced pollution. The magnitude of such benefits largely depends on the assumptions of future policies and technological change in the baseline against which they are measured, as discussed in Morgenstern (2000). For example, Smith et al. (2005) and Rao et al. (2005) assume an overall growth in environmental awareness and formulation of new environmental policies with increased affluence in the baseline scenario, and thus reduced 213
Issues related to mitigation in the long-term context
air pollution, even in the absence of any climate policies. The pace of this trend differs significantly across pollutants and baseline scenarios, and may or may not have an obvious effect on greenhouse gases. An added aspect of ancillary benefit measurement is the representation of technological options. Some emission-control technologies reduce both air pollutants and greenhouse gases, such as selective catalytic reduction (SCR) on gas boilers, which reduces not only NOx, but also N2O, CO and CH4 (IPCC, 1997). But there are also examples where, at least in principle, emission-control technologies aimed at a certain pollutant could increase emissions of other pollutants. For example, substituting more fuel-efficient diesel engines for petrol engines might lead to higher PM/black carbon emissions (Kupiainen and Klimont 2004). Thus estimating co-benefits of climate mitigation should include adequate sectoral representation of emission sources, a wide range of substitution possibilities, assumptions on technological change and a clear representation of current environmental legislation. Only a few studies have explored the longer-term ancillary benefits of climate policies. Alcamo (2002) and Mayerhofer et al. (2002) assess in detail the linkages between regional air pollution and climate change in Europe. They emphasize important co-benefits between climate policy and air pollution control but also indicate that, depending on assumptions, air pollution policies in Europe will play a greater role in air pollutant reductions than climate policy. Smith and Wigley (2006) suggest that there will be a slight reduction in global sulphur aerosols as a result of long-term multi-gas climate stabilization. Rao et al. (2005) and Smith and Wigley (2006) find that climate policies can reduce cumulative BC and OC emissions by providing the impetus for adoption of cleaner fuels and advanced technologies. In addition, the inclusion of co-benefits for air pollution can have significant impacts on the cost effectiveness of both the climate policy and air pollution policy under consideration. Van Harmelen et al. (2002) find that to comply with agreed upon or future policies to reduce regional air pollution in Europe, mitigation costs are implied, but these are reduced by 50–70% for SO2 and around 50% for NOx when combined with GHG policies. Similarly, in the shorter-term, Van Vuuren et al. (2006c) find that for the Kyoto Protocol, about half the costs of climate policy might be recovered from reduced air pollution control costs. The exact benefits, however, critically depend on how the Kyoto Protocol is implemented. The different spatial and temporal scale of greenhouse gases and air pollutants is a major difficulty in evaluating ancillary benefits. Swart et al. (2004) stress the need for new analytical bridges between these different spatial and temporal scales. Rypdal et al. (2005) suggest the possibility of including some local pollutants, such as CO and VOCs, in global climate agreement with others (e.g. NOx) and aerosols being regulated by regional agreements. It should be noted that some air pollutants, such as sulphate and carbonaceous aerosols, exert radiative forcing and thus global warming, but their contribution is uncertain. Smith and Wigley (2006) find that the attendant reduced aerosol 214
Chapter 3
cooling from sulphates can more than offset the reduction in warming that accrues from reduced GHGs. On the other hand, air pollutants such as NOx, CO and VOCs act as indirect greenhouse gases having an influence for example via their impact on OH (hydroxil) radicals and therefore the lifetime of direct greenhouse gases (e.g. methane and HFCs). Further, the climatic effects of some pollutants, such as BC and OC aerosols, remain unclear. While there has been a lot of recent research in estimating co-benefits of joint GHG and air pollution policies, most current studies do not have a comprehensive treatment of co-benefits in terms of reduction costs and the related health and climate impacts in the long-term, thus indicating the need for more research in this area. 3.3.6
Characteristics of regional and national mitigation scenarios
Table 3.7 summarizes selected national mitigation scenarios. There are broadly two types of national scenarios that focus on climate mitigation. First, there are the scenarios that study mitigation options and related costs under a given national emissions cap and trade regime. The second are the national scenarios that focus on evaluation of climate mitigation measures and policies in the absence of specific emissions targets. The former type of analysis has been mainly undertaken in the studies in the European Union and Japan. The latter type has been explored in the USA, Canada and Japan. There is also an increasing body of literature, mainly in developing countries, which analyses national GHG emissions in the context of domestic concerns, such as energy security and environmental co-benefits. Many of these developing country analyses do not explicitly address emissions mitigation. In contrast to global studies, regional scenario analyses have focused on shorter time horizons, typically up to between 2030 and 2050. A number of scenario studies have been conducted for various countries within Europe. These studies explore a wide range of emission caps, taking into account local circumstances and potentials for technology implementation. Many of these studies have used specific burden-sharing allocation schemes, such as the contraction and convergence (C&C) approach (GCI, 2005) for calculating the allocation of worldwide emissions to estimate national emissions ceilings. The UK’s Energy White Paper (DTI, 2003) examined measures to achieve a 60% reduction in CO2 emissions by 2050 as compared to the current level. Several studies have explored renewable energy options, for example, the possibility of expanding the share of renewable energy and the resulting prospects for clean hydrogen production from renewable energy sources in Germany (Deutscher Bundestag, 2002; Fischedick and Nitsch, 2002; Fischedick et al., 2005). A European study, the COOL project (Tuinstra et al., 2002; Treffers et al., 2005), has explored the possibilities of reducing emissions in the Netherlands by 80% in 2050 compared to 1990 levels. In France, the Inter Ministerial Task Force on Climate Change (MIES, 2004) has examined mitigation options that
Chapter 3
Issues related to mitigation in the long-term context
Table 3.7: National scenarios with quantification up to 2050 and beyond.
Country
Author/Agency
Model
Time horizon
Target variables
Base year
Target of reduction to the value of the base year
USA
Hanson et al. (2004)
AMIGA1
2000-2050
-
2000
(about 44% in 2050)
Canada
Natural Resource Canada (NRCan) (2000)
N.A.
2000-2050
GHG emissions
2000
(53% in 2050)
India
Nair et al. (2003)
Integrated modelling framework1,3
1995-2100
Cumulative CO2 emissions
Shukla et al. (2006)
ERB2
1990-2095
CO2 emissions
Chen (2005)
MARKALMACRO2,3
2000-2050
CO2 emissions
Reference
5-45% in 2050
Van Vuuren et al. (2003)
IMAGE/TIMER2,4
1995-2050
GHG emissions
1995
-
Jiang and Xiulian (2003)
IPAC-emission2,3
1990-2100
GHG emissions
1990
-
1990-2050
GHG emissions
1990
80% in 2050
China Netherlands
Tuinstra et al. (2002) (COOL)
550 ppmv, 650 pmv
550 ppmv
Germany
Deutscher Bundestag (2002)
WI4, IER
2000-2050
CO2 emissions
1990
80% in 2050
UK
Department of Trade and Industry (DTI) (2003)
MARKAL3
2000-2050
CO2 emissions
2000
45%, 60%, 70% in 2050
France
Interministerial Task Force on Climate Change (MIES) (2004)
N.A.
2000-2050
CO2 emissions
2000
0.5 tC/cap (70% in 2050)
Australia
Ahammad et al. (2006)
GTEM1
2000-2050
GHG emissions
1990
50% in 2050
Japan LCS Project (2005)
AIM/Material1
2000-2050
CO2 emissions
1990
60-80% in 2050
Ministry of Economy, Trade and Industry (2005)
GRAPE3
2000-2100
CO2/GDP
2000
1/3 in 2050, 1/10 in 2100
Masui et al. (2006)
AIM/Material1
2000-2050
CO2 emissions
1990
74% in 2050
Akimoto et al. (2004)
Optimization model3
2000-2050
CO2 emissions
2000
0.5% /yr (21% in 2050)
Japan Atomic Industrial Forum (JAIF) (2004)
MARKAL3
2000-2050
CO2 emissions
2010 (1990)
40% in 2050
Japan
MENOCO4
Notes: model types: 1: CGE-type top-down model, 2: other type of top-down model, 3: bottom-up technology model with optimization, 4: bottom-up technology model without optimization.
could lead to significant reductions in per capita emissions intensity. Savolainen et al. (2003) and Lehtila et al. (2005) have conducted a series of scenario analyses in order to assess technological potentials in Finland for a number of options that include wind power, electricity-saving possibilities in households and office appliances, and emission abatement of fluorinated GHGs. Scenario studies in the USA have explored the implications of climate mitigation for energy security (Hanson et al., 2004). For example, Mintzer et al. (2003) developed a set of scenarios describing three divergent paths for US energy supply and use from 2000 through 2035. These scenarios were used to identify key technologies, important energy policy decisions, and strategic investment choices that may enhance energy security, environmental protection, and economic development.
A wide range of scenario studies have also been conducted to estimate potential emissions reductions and associated costs for Japan. For example, Masui et al. (2006) developed a set of scenarios that explore the implications of severe emissions cutbacks of between 60 and 80% CO2 by 2050 (compared to 1990). Another important study by Akimoto et al. (2004) evaluates the possibilities of introducing the CCS option and its economic implications for Japan. National scenarios pertaining to developing countries such as China and India mainly analyze future emission trajectories under various scenarios that include considerations such as economic growth, technology development, structure changes, globalization of world markets, and impacts of mitigation options. Unlike the scenarios developed for the European countries, most of the developing-country scenarios do not 215
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Table 3.8: Developed countries scenarios with more than 40% reduction (compared to 2000 emissions), and some Chinese scenarios: CO2 emission changes from 2000 to
2050; Energy intensity and carbon intensity in 2000, and their changes from 2000 up to 2050. (A) CO2 emission changes, energy intensity, and carbon intensity in 2000.
Country
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Notes: Data sources: China: Jiang and Xulian (2003), Van Vuuren et al. (2003), Japan: Masui et al. (2006), Akimoto et al. (2004), JAIF (2004), Germany: Deutscher Bundestag (2002), France: MIES (2004), UK: DTI (2003), USA: Hanson et al. (2004). The coloured areas show the range of the global model results of EMF-21 with the target of 4.5 W/m2. The range of EU-15 is shown for European countries
specify limits on emissions (Van Vuuren et al., 2003; Jiang and Xiulian, 2003). Chen (2005) shows that structural change can be a more important contributor to CO2 reduction than technology efficiency improvement. The scenario construction for India pays specific attention to developing-country dynamics, underlying the multiple socio-economic transitions during the century, including demographic transitions (Shukla et al., 2006). Nair et al. (2003) studied potential shifts away from coal-intensive baselines to the use of natural gas and renewables. There are several country scenarios that consider drastic reduction of CO2 emissions. In these studies, which consider 60–80% reductions of CO2 in 2050, rates of improvement in 216
energy intensity and carbon intensity increase by about two to three times their historical levels (Kawase et al., 2006). Table 3.8 summarizes scenarios with more than 40% CO2 reductions (2000–2050) in several developed countries. The table also includes some Chinese scenarios with deep cuts of CO2 emissions compared to the reference cases. Physical indicators of the Chinese economy show that current efficiency is below the OECD average in most sectors, thus indicating a greater scope for improvement (Jiang and Xiulian, 2003). It should be noted that comparing the energy intensity of the Chinese economy on the basis of market exchanges rates to OECD averages suggests even larger differences, but this is
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Figure 3.31: Relationship between carbon prices and CO2 reduction from baseline in 2050 in selected countries taken from the literature published since the TAR. Note: The red box shows the range between the 25th and 75th percentile of the scenarios for each price range. EECCA= Countries of Eastern Europe, the Caucasus and Central Asia.
misleading given the differences in purchasing power (PPPcorrected energy intensity data gives a somewhat better basis for comparison, but still suffers from uncertainty about the data and different economic structures).
carbon intensity reduction in the first half of the 21st century, but that carbon intensity reduction becomes more dominant in the latter half of the century (Hanaoka et al., 2006).
In the countries with low energy intensity levels in 2000 (such as Japan, Germany and France), the scenarios specify solutions for meeting long-term drastic reduction goals by carbon intensity improvement measures, such as shifting to natural gas in the UK, renewable energy in the Netherlands, and CCS in certain scenarios in France, Germany, the UK and the USA. France has a scenario where CCS accounts for 100% of carbon intensity improvement. Most of the scenarios with drastic CO2 reductions for the USA and the UK assume the introduction of CCS.
3.3.6.1
The light yellow coloured area in Table 3.8 shows the range of the global model results of EMF-21 with the stabilization target of 4.5 W/m2. Most country results show the need for greater improvement in carbon intensity during 2000 to 2050 compared to the global results. The results of scenario analysis since the TAR show that energy intensity improvement is superior to
Costs of mitigation in regional and country scenarios
Figure 3.31 shows the relationship between carbon prices and the CO2 mitigation rates from the baseline in 2050 in some major countries and regions such as the USA, Japan, EU-15, India, China, Former Soviet Union (FSU) and Eastern Europe, taken from the literature since the TAR (Hanaoka et al., 2006). In the developing countries there are many scenarios where relatively high CO2 reductions are projected even with low carbon prices. With high prices in the range of 100-150 US$/tCO2 (in 2000 US dollars) more CO2 reductions are expected in China and India than in developed countries when the same level of carbon price is applied.
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3.4 The role of technologies in long-term mitigation and stabilization: research, development, deployment, diffusion and transfer Technology is among the central driving forces of GHG emissions. It is one of the main determinants of economic development, consumption patterns and thus human well-being. At the same time, technology and technological change offer the main possibilities for reducing future emissions and achieving the eventual stabilization of atmospheric concentrations of GHGs (see Chapter 2, Section 2.7.1.2, which assesses the role of technology in climate change mitigation, including longterm emissions and stabilization scenarios). The ways in which technology reduces future GHG emissions in long-term emission scenarios include: • Improving technology efficiencies and thereby reducing emissions per unit service (output). These measures are enhanced when complemented by energy conservation and rational use of energy. • Replacing carbon-intensive sources of energy by less intensive ones, such as switching from coal to natural gas. These measures can also be complemented by efficiency improvements (e.g. combined cycle natural gas power plants are more efficient than modern coal power plants) thereby further reducing emissions. • Introducing carbon capture and storage to abate uncontrolled emissions. This option could be applied at some time in the future, in conjunction with essentially all electricity generation technologies, many other energy conversion technologies and energy-intensive processes using fossil energy sources as well as biomass (in which case it corresponds to net carbon removal from the atmosphere). • Introducing carbon-free renewable energy sources ranging from a larger role for hydro and wind power, photovoltaics and solar thermal power plants, modern biomass (that can be carbon-neutral, resulting in zero net carbon emissions) and other advanced renewable technologies. • Enhancing the role of nuclear power as another carbonfree source of energy. This would require a further increase in the nuclear share of global energy, depending on the development of ‘inherently’ safe reactors and fuel cycles, resolution of the technical issues associated with long-term storage of fissile materials and improvement of national and international non-proliferation agreements. • New technology configurations and systems, e.g. hydrogen as a carbon-free carrier to complement electricity, fuel cells and new storage technologies. • Reducing GHG and CO2 emissions from agriculture and land use in general critically depends on the diffusion of
Chapter 3
new technologies and practices that could include less fertilizer-intensive production and improvement of tillage and livestock management. Virtually all scenarios assume that technological and structural changes occur during this century, leading to relative reductions in emissions compared to the hypothetical case of attempting to ‘keep’ emissions intensities of GDP and structure the same as today (see Chapter 2, Section 2.7.1.1, which discusses the role of technology in baseline scenarios). Figure 3.32 shows such a hypothetical range of cumulative emissions under the assumption of ‘freezing’ technology and structural change in all scenarios at current levels, but letting populations change and economies develop as assumed in the original scenarios (Nakicenovic et al., 2006). To show this, the energy intensity of GDP and the carbon intensity of energy are kept constant. The bars in the figure indicate the central tendencies of the scenarios in the literature by giving the cumulative emissions ranges between the 25th and the 75th percentile of the scenarios in the scenario database.21 The hypothetical cumulative emissions (without technology and structural change) range from about 9000 (25th percentile) to 12000 (75th percentile), with a median of about 10400 GtCO2 by 2100. The next bar in Figure 3.32 shows cumulative emissions by keeping carbon intensity of energy constant while allowing energy intensity of GDP to evolve as originally specified in the underlying scenarios. This in itself reduces the cumulative emissions substantively, by more than 40% to almost 50% (75th and 25th percentiles, respectively). Thus, structural economic changes and more efficient use of energy lead to significant reductions of energy requirements across the scenarios as incorporated in the baselines, indicating that the baseline already includes vigorous carbon saving. In other words, this means that many new technologies and changes that lead to lower relative emissions are assumed in the baseline. Any mitigation measures and policies need to go beyond these baseline assumptions. The next bar in Figure 3.32 also allows carbon intensities of energy to change as originally assumed in the underlying scenarios. Again, the baseline assumptions lead to further and substantial reductions of cumulative emissions, by some 13% to more than 20% (25th and 75th percentile, respectively), or less than half the emissions, as compared to the case of no improvement in energy or carbon intensities. This results in the original cumulative emissions as specified by reference scenarios in the literature, from 4050 (25th percentile) to 5400 (75th percentile), with a median of 4730 GtCO2 by 2100. It should be noted that this range is for the 25th to the 75th percentile only. In contrast, the full range of cumulative emissions across 56 scenarios in the database is from 2075 to 7240 GtCO2.22
21 The outliers, above the 75th and below the 25th percentile are discussed in more detail in the subsequent sections. 22 The cumulative emissions range represents a huge increase compared to the historical experience. Cumulative global emissions were about 1100 GtCO2 from the 1860s to today, a very small fraction indeed of future expected emissions across the scenarios.
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Figure 3.32: Median, 25th and 75th percentile of global cumulative carbon emissions by 2100 in the scenarios developed since 2001. Note: The range labelled ‘frozen technology’ refers to hypothetical futures without improvement in energy and carbon intensities in the scenarios; the range labelled ‘frozen energy intensity’ refers to hypothetical futures where only carbon intensity of energy is kept constant, while energy intensity of GDP is left the same as originally assumed in scenarios; the range labelled CO2 baseline refer to the 83 baseline scenarios in the database, while the region labelled CO2 intervention includes 211 mitigation and/or stabilization scenarios. Source: After Nakicenovic et al. (2006)
The next and final step is to compare the cumulative emissions across baseline scenarios with those in the mitigation and stabilization variants of the same scenarios. Figure 3.32 shows (in the last bar) yet another significant reduction of future cumulative emissions from 2370 to 3610 (corresponding to the 25th to the 75th percentile of the full scenario range), with a median of 3010 GtCO2 by 2100. This corresponds to about 70% emissions reduction across mitigation scenarios, compared to the hypothetical case of no changes in energy and carbon intensities and still a large, or about a 30%, reduction compared to the respective baseline scenarios.23 This illustrates the importance of technology and structural changes, both in reference and mitigation scenarios. However, this is an aggregated illustration across all scenarios and different mitigation levels for cumulative emissions. Thus, it is useful to also give a more specific illustrative example. Figure 3.33 gives such an illustration by showing the importance of technological change assumptions in both reference and mitigation scenarios for a 550 ppmv concentration target based on four SRES scenarios. Such analyses are increasingly becoming available. For instance, Placet et al. (2004) provide a detailed study of possible technology development pathways under climate stabilization for the US government Climate Change Technology Program. To illustrate the importance of technological change, actual projected scenario values in the original SRES no-climate policy scenarios are compared with a hypothetical case with frozen 1990 structures and technologies for both energy supply and end-use. The difference (denoted by a grey shaded area in Figure 3.33) illustrates the impact of technological change, which leads to improved efficiency and ‘decarbonization’ in energy systems already incorporated into the baseline emission scenario.
The impacts of technological options leading to emission reductions are illustrated by the colour-shaded areas in Figure 3.33, regrouped into three categories: demand reductions (e.g. through deployment of more efficient end-use technologies, such as lighting or vehicles), fuel switching (substituting high-GHG-emitting technologies for low- or zero-emitting technologies such as renewables or nuclear), and finally, CO2 capture and storage technologies. The mix in the mitigative technology portfolio required to reduce emissions from the reference scenario level to that consistent with the illustrative 550 ppmv stabilization target varies as a function of the baseline scenario underlying the model calculations (shown in Figure 3.33), as well as with the degree of stringency of the stabilization target adopted (not shown in Figure 3.33). An interesting finding from a large number of modelling studies is that scenarios with higher degrees of technology diversification (e.g. scenario A1B in Figure 3.33) also lead to a higher degree of flexibility with respect of meeting alternative climate (e.g. stabilization) targets and generally also to lower overall costs compared with less diversified technology scenarios. This illustrative example also confirms the conclusion reached in Section 3.3 that was based on a broader range of scenario literature. This brief assessment of the role of technology across scenarios indicates that there is a significant technological change and diffusion of new and advanced technologies already assumed in the baselines and additional technological change ‘induced’ through various policies and measures in the mitigation scenarios. The newer literature on induced technological change assessed in the previous sections, along with other scenarios (e.g. Grübler et al., 2002; and Köhler et al., 2006, see also Chapter 11), also affirms this conclusion. 3.4.1 3.4.1.1
Carbon-free energy and decarbonization Decarbonization trends
Decarbonization denotes the declining average carbon intensity of primary energy over time. Although decarbonization of the world’s energy system is comparatively slow (0.3% per year), the trend has persisted throughout the past two centuries (Nakicenovic, 1996). The overall tendency towards lower carbon intensities is due to the continuous replacement of fuels with high carbon content by those with low carbon content; however, intensities are currently increasing in some developing regions. In short- to medium-term scenarios such a declining tendency for carbon intensity may not be as discernable as across the longer-term literature, e.g. in the World Energy Outlook 2004 (IEA, 2004), the reference scenario to 2030 shows the replacement of gas for other fossil fuels as well as cleaner fuels due to limited growth of nuclear and bioenergy. Another effect contributing towards reduced carbon intensity of the economy is the declining energy requirements per unit
23 In comparison, the full range of cumulative emissions from mitigation and stabilization scenarios in the database runs from 785 to 6794 GtCO2.
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Figure 3.33: Impact of technology on global carbon emissions in reference and climate mitigation scenarios. Note: Global carbon emissions (GtC) in four scenarios developed within the IPCC SRES and TAR (A2, B2 top and bottom of left panel; A1FI and A1B top and bottom of right panel). The grey-shaded area indicates the difference in emissions between the original no-climate policy reference scenario compared with a hypothetical scenario assuming frozen 1990 energy efficiency and technology, illustrating the impact of technological change incorporated already into the reference scenario. Colour-shaded areas show the impact of various additional technology options deployed in imposing a 550 ppmv CO2 stabilization constraint on the respective reference scenario, including energy conservation (blue), substitution of high-carbon by low- or zero-carbon technologies (orange), as well as carbon capture and sequestration (black). Of particular interest are the two A1 scenarios shown on the right-hand side of the panel that share identical (low) population and (high) economic growth assumptions, thus making differences in technology assumptions more directly comparable. Source: Adapted from Nakicenovic et al. (2000), IPCC (2001a), Riahi and Roehrl (2001), and Edmonds (2004).
of GDP, or energy intensity of GDP. Globally, energy intensity has been declining more rapidly than carbon intensity of energy (0.9% per year) during the past two centuries (Nakicenovic, 1996). Consequently, carbon intensity of GDP declined globally at about 1.2% per year. The carbon intensity of energy and energy intensities of GDP were shown in Section 3.2 of this chapter, Figure 3.6, for the full scenario sample in the scenario database compared to the newer (developed after 2001) non-intervention scenarios. As in Sections 3.2 and 3.3, the range of the scenarios in the literature until 2001 is compared with recent projections from scenarios developed after 2001 (Nakicenovic et al., 2005). The majority of the scenarios in the literature portray a similar and persistent decarbonization trend as observed in the past. In particular, the medians of the scenario sets indicate energy decarbonization rates of about 0.9% (pre-2001 literature median) and 0.6% (post-2001 median) per year, which is a significantly more rapid decrease compared to the historical rates of about 0.3% per year. Decarbonization of GDP is also more rapid (about 2.5% per year for both pre- and post-2001 220
literature medians) compared with the historical rates of about 1.2% per year. As expected, the intervention and stabilization scenarios have significantly higher decarbonization rates and the post-2001 scenarios include a few with significantly more rapid decarbonization of energy, even extending into the negative range. This means that towards the end of the century these more extreme decarbonization scenarios foresee net carbon removal from the atmosphere, e.g. through carbon capture and storage in conjunction with large amounts of biomass energy. Such developments represent a radical paradigm shift compared to the current and more short-term energy systems, implying significant and radical technological changes. In contrast, the scenarios that are most intensive in the use of fossil fuels lead to practically no reduction in carbon intensity of energy, while all scenarios portray decarbonization of GDP. For example, the upper boundary of the recent scenarios developed after 2001 depict slightly increasing (about 0.3% per year) carbon intensities of energy (A2 reference scenario, Mori (2003), see Figure 3.8, comparing carbon emissions across scenarios in the literature presented in Section 3.2). Most notably, a few scenarios developed before 2001 follow an opposite
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3.4.1.2
Key factors for carbon-free energy and decarbonization development
All of the technological options assumed to contribute towards further decarbonization and reduction of future GHG emissions require further research and development (R&D) to improve their technical performance, reduce costs and achieve social acceptability. In addition, deployment of carbon-saving technologies needs to be applied at ever-larger scales in order to benefit from potentials of technological learning that can result in further improved costs and economic characteristics of new technologies. Most importantly, appropriate institutional and policy inducements are required to enhance widespread diffusion and transfer of these technologies. Full replacement of dominant technologies in the energy systems is generally a long process. In the past, the major energy technology transitions have lasted more than half a century, such as the transition from coal as the dominant energy source
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The highest rates of decarbonization of energy (up to 2.5% per year for the recent scenarios) are from scenarios that include a complete transition in the energy system away from carbonintensive fossil fuels. Clearly, the majority of these scenarios are intervention scenarios, although some non-intervention scenarios show drastic reductions in CO2 intensities due to reasons other than climate policies (e.g. the combination of sustainable development policies and technology push measures to promote renewable hydrogen systems). The relatively fast decarbonization rate of intervention scenarios is also illustrated by the median of the post-2001 intervention scenarios, which depict an average rate of improvement of 1.1% per year over the course of the century, compared to just 0.3% for the non-intervention scenarios. Note, nevertheless, that the modest increase in carbon intensity of energy improvements in the intervention scenarios above the 75th percentile of the distribution of the recent scenarios. The vast majority of these scenarios represent sensitivity analysis; have climate policies for mitigation of non-CO2 greenhouse gas emissions (methane emissions policies: Reilly et al., 2006); or have comparatively modest CO2 reductions measures, such as the implementation of a relatively minor carbon tax of 10 US$/tC (about 2.7 US$/tCO2) over the course of the century (e.g. Kurosawa, 2004). Although these scenarios are categorized according to our definition as intervention scenarios, they do not necessarily lead to the stabilization of atmospheric CO2 concentrations.
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path compared to other scenarios: decarbonization of primary energy with decreasing energy efficiency until 2040, followed by rapidly increasing ratios of CO2 per unit of primary energy after 2040 – in other words, recarbonization. In the long term, these scenarios lie well above the range spanned by the new scenarios, indicating a shift towards more rapid CO2 intensity improvements in the recent literature (Nakicenovic et al., 2006). In contrast, there are just a very few scenarios in the post-2100 literature that envisage increases in carbon intensity of energy.
Figure 3.34: Deployment of primary energy technologies across pre-2001 scenarios by 2030 and 2100: Left-side ‘error’ bars show baseline (non-intervention) scenarios and right-side ones show intervention and stabilization scenarios. The full ranges of the distributions (full vertical line with two extreme tic marks), the 25th and 75th percentiles (blue area) and the median (middle tic mark) are also shown.
in the world some 80 years ago, to the dominance of crude oil during the 1970s. Achieving such a transition in the future towards lower GHG intensities is one of the major technological challenges addressed in mitigation and stabilization scenarios. Figures 3.34 and 3.35 show the ranges of energy technology deployment across scenarios by 2030 and 2100 for baseline (non-intervention) and intervention (including stabilization) scenarios, respectively. The deployment of energy technologies in general, and of new technologies in particular, is significant indeed, even through the 2030 period, but especially by 2100. The deployment ranges should be compared with the current total global primary energy requirements of some 440 EJ in 2000. Coal, oil and gas reach median deployment levels ranging from some 150 to 250 EJ by 2030. The variation is significantly higher by 2100, but even medians reach levels of close to 600 EJ for coal in reference scenarios, thereby exceeding by 50% the current deployment of all primary energy technologies in the world. Deployment of nuclear and biomass is comparatively lower, in the range of about 50–100 EJ by 2030 and up to ten times as much by 2100. This all indicates that radical technological changes occur across the range of scenarios. The deployment ranges are large for each of the technologies but do not differ much when comparing the pre-2001 with post2001 scenarios over both time periods, up to 2030 and 2100. Thus, while technology deployments are large in the mean and variance, the patterns have changed little in the new (compared 221
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from energy and other sources. Innovation in energy technology will be integral to meeting the objective of emission reduction. Investment and incentives will be needed for all components of the innovation system – research and development (R&D), demonstration, market introduction and its feedback to development, flows of information and knowledge, and the scientific research that could lead to new technological advances. Thus, sufficient investment will be required to ensure that the best technologies are brought to market in a timely manner. These investments, and the resulting deployment of new technologies, provide an economic value. Model calculations enable economists to quantify the value of improved technologies as illustrated for two technologies in Figure 3.36.
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with the older) scenarios. What is significant in both sets of literature is the radically different structure and portfolio of technologies between baseline and stabilization scenarios. Mitigation generally means significantly less coal, somewhat less natural gas and consistently more nuclear and biomass. What cannot be seen from this comparison, due to the lack of data and information about the scenarios, is the extent to which carbon capture and storage is deployed in mitigation scenarios. However, it is very likely that most of the coal and much of the natural gas deployment across stabilization scenarios occurs in conjunction with carbon capture and storage. The overall conclusion is that mitigation and stabilization in emissions scenarios have a significant inducement on diffusion rates of carbon-saving and zero-carbon energy technologies. 3.4.2
These results lend further credence to technology R&D and deployment incentives policies (for example prices24) as ‘hedging’ strategies addressing climate change. However, given the current insufficient understanding of the complexity of driving forces underlying technological innovation and cost improvements, cost-benefit or economic ‘return on investment’, calculations have (to date) not been attempted in the literature, due at least in part to a paucity of empirical technology-specific data on R&D and niche-market deployment expenditures and the considerable uncertainties involved in linking ‘inputs’ (R&D and market stimulation costs) to ‘outputs’ (technology improvements and cost reductions). 3.4.3
RD&D and investment patterns
As mentioned in Chapter 2, the private sector is leading global research and development of technologies that are close to market deployment, while public funding is essential for the longer term and basic research. R&D efforts in the energy area are especially important for GHG emissions reduction. Accelerating the availability of advanced and new technologies will be central to greatly reducing CO2 emissions 24 See Newell et al., 1999.
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Generally, economic benefits from improved technology increase non-linearly with: 1. The distance to current economic characteristics (or the ones assumed to be characteristic of the scenario baseline). 2. The stringency of environmental targets. 3. The comprehensiveness and diversity of a particular technology portfolio considered in the analysis. Thus, the larger the improvement of future technology characteristics compared to current ones, the lower the stabilization target, and the more comprehensive the suite of available technologies, the greater will be the economic value of improvements in technology.
3.4.3.1
Dynamics and drivers of technological change, barriers (timing of technology deployment, learning) Summary from the TAR
The IPCC-TAR concluded that reduction of greenhouse gas emissions is highly dependent on both technological innovation and implementation of technologies (a conclusion broadly confirmed in Chapter 2, Section 2.7.1). However, the rate of introduction of new technologies, and the drivers for adoption are different across different parts of the world, particularly
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Figure 3.36: The value of improved technology. Note: Modelling studies enable experts to calculate the economic value of technology improvements that increase particularly drastically with increasing stringency of stabilization targets (750, 650, 500, and 450 ppmv, respectively) imposed on a reference scenario (modelling after the IS92a scenario in this particular modelling study). Detailed model representation of technological interdependencies and competition and substitution is needed for a comprehensive assessment of the economic value of technology improvements. Left panel: cost savings (billions of 1996 US$) compared to the reference scenario when lowering the costs of solar photovoltaics (PV) from a reference value of 9 US cents per kWh (top) by 1, 3, 4, and 6 cents/kWh, respectively. For instance, the value of reducing PV costs from 9 to 3 cents per kWh could amount to up to 1.5 trillion US$ in an illustrative 550 ppmv stabilization scenario compared to the reference scenario in which costs remain at 9 cents/kWh). Right panel: cost savings resulting from availability of an ever larger and diversified portfolio of carbon capture and sequestration technologies. For instance, adding soil carbon sequestration to the portfolio of carbon capture and sequestration technology options (forest-sector measures were not included in the study) reduces costs by 1.1 trillion US$ in an illustrative 450 ppmv stabilization scenario. Removing all carbon capture sequestration technologies would triple the costs of stabilization for all concentration levels analyzed. Source: GTSP, 2001.
in industrial market economies, economies in transition and developing countries. To some extent this is reflected in global emissions scenarios as they often involve technological change at a level that includes a dozen or so world regions. This usually involves making more region-specific assumptions about future performance, costs and investment needs for new and lowcarbon technologies. There are multiple policy approaches to encourage technological innovation and change. Through regulation of energy markets, environmental regulations, energy efficiency standards, financial and other market-based incentives, such as energy and emission taxes, governments can induce technology changes and influence the level of innovations. In emissions scenarios, this is reflected in assumptions about policy instruments such as taxes, emissions permits, technology standards, costs, and lower and upper boundaries of technology diffusion. 3.4.3.2
Dynamics of technology
R&D, technological learning, and spillovers are the three broad categories of drivers behind technological change. These are discussed in Chapter 2, Section 2.7, and Chapter 11, Section 11.5. The main conclusion is that, on the whole, all
three of the sources of induced technological change (ITC) play important roles in technological advance. Here, we focus on the dynamics of technology and ITC in emissions and stabilization scenarios. Emissions scenarios generally treat technological change as an exogenous assumption about costs, market penetration and other technology characteristics, with some notable exceptions such as in Gritsevskyi and Nakicenovic (2000). Hourcade and Shukla (2001), in their review of scenarios from top-down models, indicate that technology assumptions are a critical factor that affects the timing and cost of emission abatement in the models. They identify widely differing costs of stabilization at 550 ppmv by 2050, of between 0.2 and 1.75% of GDP, mainly influenced by the size of the emissions in the baseline. The International Modelling Comparison Project (IMCP) (Edenhofer et al., 2006) compared the treatment relating to technological change in many models covering a wide range of approaches. The economies for technological change were simulated in three groups: effects through R&D expenditures, learning-by-doing (LBD) or specialization and scale. IMCP finds that ITC reduces costs of stabilization, but in a wide range, depending on the flexibility of the investment decisions and the range of mitigation options in the models. It should be noted, 223
Issues related to mitigation in the long-term context
however, that induced technological change is not a ‘free lunch’, as it requires higher upfront investment and deployment of new technologies in order to achieve cost-reductions thereafter. This can lead to lower overall mitigation costs. All models indicate that real carbon prices for stabilization targets rise with time in the early years, with some models showing a decline in the optimal price after 2050 due to the accumulated effects of LBD and positive spillovers on economic growth. Another robust result is that ITC can reduce costs when models include low carbon energy sources (such as renewables, nuclear, and carbon capture and sequestration), as well as energy efficiency and energy savings. Finally, policy uncertainty is seen as an issue. Long-term and credible abatement targets and policies will reduce some of the uncertainties around the investment decisions and are crucial to the transformation of the energy system. ITC broadens the scope of technology-related policies and usually increases the benefits of early action, which accelerates deployment and cost-reductions of low-carbon technologies (Barker et al., 2006; Sijm, 2004; Gritsevskyi and Nakicenovic, 2000). This is due to the cumulative nature of ITC as treated in the new modelling approaches. Early deployment of costly technologies leads to learning benefits and lower costs as diffusion progresses. In contrast, scenarios with exogenous technology assumptions imply waiting for better technologies to arrive in the future, though this too may result in reduced costs of emission reduction (European Commission, 2003). Other recent work also confirms these findings. For example, Manne and Richels (2004) and Goulder (2004) also found that ITC lowers mitigation costs and that more extensive reductions in GHGs are justified than with exogenous technical change. Nakicenovic and Riahi (2003) noted how the assumption about the availability of future technologies was a strong driver of stabilization costs. Edmonds et al. (2004a) studied stabilization at 550 ppmv CO2 in the SRES B2 world using the MiniCAM model and showed a reduction in costs of a factor of 2.5 in 2100 using a baseline incorporating technical change. Edmonds et al. consider advanced technology development to be far more important as a driver of emission reductions than carbon taxes. Weyant (2004) concluded that stabilization will require the large-scale development of new energy technologies, and that costs would be reduced if many technologies are developed in parallel and there is early adoption of policies to encourage technology development. The results from the bottom-up and more technology-specific modelling approaches give a different perspective. Following the work of the IIASA in particular, models investigating induced technical change emerged during the mid- and late1990s. These models show that ITC can alter results in many ways. In the previous sections of this chapter the authors have also illustrated that the baseline choice is crucial in determining the nature (and by implication also the cost) of stabilization. 224
Chapter 3
However, this influence is itself largely due to the different assumptions made about technological change in the baseline scenarios. Gritsevskyi and Nakicenovic (2000) identified some 53 clusters of least-cost technologies, allowing for endogenous technological learning with uncertainty. This suggests that a decarbonized economy may not cost any more than a carbonintensive one, if technology learning curves are taken into account. Other key findings are that there is a large diversity across alternative energy technology strategies, a finding that was confirmed in IMCP (Edenhofer et al., 2006). These results suggest that it is not possible to choose an ‘optimal’ direction for energy system development. Some modelling reported in the TAR suggests that a reduction (up to 5 GtC a year) by 2020 (some 50% of baseline projections) might be achieved by current technologies, half of the reduction at no direct cost, the other half at direct costs of less than 100 US$/tC-equivalent (27 US$/tCO2-eq). 3.4.3.3
Barriers to technology transfer, diffusion and deployment for long-term mitigation
Chapter 2, Section 2.7.2 includes a discussion of the barriers to development and commercialization of technologies. Barriers to technology transfer vary according to the specific context from sector to sector and can manifest themselves differently in developed and developing countries, and in economies-intransition (EITs). These barriers range from a lack of information; insufficient human capabilities; political and economic barriers (such as the lack of capital, high transaction costs, lack of full cost pricing, and trade and policy barriers); institutional and structural barriers; lack of understanding of local needs; business limitations (such as risk aversion in financial institutions); institutional limitations (such as insufficient legal protection); and inadequate environmental codes and standards. 3.4.3.4
Dynamics in developing countries and timing of technology deployment
National policies in developing countries necessarily focus on more fundamental priorities of development, such as poverty alleviation and providing basic living conditions for their populations, and it is unlikely that short-term national policies would be driven by environmental concerns. National policies driven by energy security concerns can, however, have strong alignment with climate goals. The success of policies that address short-term development concerns will determine the pace at which the quality of life in the developing and the developed world converges over the long term. In the long term, the key drivers of technological change in developing countries will depend on three ‘changes’ that are simultaneous and inseparable within the context of development: exogenous behavioural changes or changes in social infrastructure; endogenous policies driven by ‘development goals’; and any induced change from climate policies (Shukla et al., 2006).
Issues related to mitigation in the long-term context
An iterative risk-management framework to articulate options
Previous IPCC reports conclude that climate change decisionmaking is not a once-and-for-all event, but an iterative riskmanagement process that is likely to take place over decades, where there will be opportunities for learning and mid-course corrections in the light of new information ( Lempert et al., 1994; Keller et al., 2006). This iterative process can be described using a decision tree (Figure 3.37), where the square nodes represent decisions, the circles represent the reduction of uncertainty and the arrows indicate the range of decisions and outcomes. Some nodes summarize today’s options – how much should be invested in mitigation, in adaptation, in expanding mitigative and adaptive capacity, or in research to reduce uncertainty? Other nodes represent opportunities to learn and make midcourse corrections. This picture is a caricature of real decision processes, which are continuous, overlapping and iterative.
L
CT
A
3.5.1.1
Efficacy of investments in previous period Development path Climate Change Climate Impacts Demographic Change
LE
A key question for policy is what combination of short-term and long-term actions will minimize the total costs of climate change, in whatever form these costs are expressed, across mitigation, adaptation and the residual climate impacts that society is either prepared or forced to tolerate. Although there are different views on the form and dynamics of such tradeoffs in climate policies, there is a consensus that they should be aligned with (sustainable) development policies, since the latter determine the capacity to mitigate and to adapt in the future (TAR, Hourcade and Shukla, 2001). In all cases, policy decisions will have to be made with incomplete understanding of the magnitude and timing of climate change, of its likely consequences, and of the cost and effectiveness of response measures.
Mitigation Adaption Technology Science
Mitigation Adaption Technology Science
N
The interaction between mitigation and adaptation, an iterative climate policy process
Responses to climate change include a portfolio of measures: a. Mitigation – actions that reduce net carbon emissions and limit long-term climate change. b. Adaptation – actions that help human and natural systems to adjust to climate change. c. Research on new technologies, on institutional designs and on climate and impacts science, which should reduce uncertainties and facilitate future decisions (Richels et al., 2004; Caldeira et al., 2003; Yohe et al., 2004).
previous period
Development path Climate Change Climate Impacts Demographic Change
A T
3.5.1
RN Efficacy of A E investments in
C
3.5 Interaction between mitigation and adaptation, in the light of climate change impacts and decision-making under long-term uncertainty
AR
Chapter 3
Figure 3.37: The Iterative Nature of the Climate Policy Process.
However, it is useful to conceptually put the many determinants of any short-term strategy in a context of progressive resolution of uncertainty. 3.5.1.2
Qualitative insights into interactions between mitigaton, adaptation and development
Until recently, a main focus in the policy and integrated assessment literature has been on comparing mitigation costs and avoided damages. Since the TAR, attention has shifted towards the interaction between mitigation and adaptation in reducing damages in a risk-management framework. This has accompanied a growing realization that some climate change in the coming decades is inevitable. Limited treatment of adaptation in climate policy assessments is still a problem and a number of reasons explain this. First, the focus of the international climate change negotiations has largely been on mitigation (perhaps because attention to adaptation could be viewed as ‘giving up’ on mitigation) even though the importance of adaptation is underlined in Article 4 of the UNFCCC and Article 10 of the Kyoto Protocol. Second, adaptation is largely undertaken at the local scale, by individual households, farmers, companies or local governments; it is thus difficult to target through coordinated international incentives, and is more complicated to handle quantitatively by models in global scenarios. Third, it is difficult to generalize the ways that individuals or communities are likely to adapt to specific impacts. However, the literature is evolving quickly and recent work is available in a number of regions; for example, in Finland (Carter et al., 2005), the UK (West and Gawith, 2005), Canada (Cohen et al., 2004) and the USA (e.g. California, Hayhoe et al., 2004). 225
Issues related to mitigation in the long-term context
Despite the scarcity of global systematic assessments (Tol, 2005a), some interesting insights into the interaction between adaptation and mitigation emerge from recent regional-scale studies. Some adaptation measures are ‘no-regret’ measures and should be undertaken anyway (Agrawala, 2005), such as preservation of mangroves in coastal zones, which provide a buffer for increased coastal flood risk due to climate change and help to maintain healthy marine ecosystems (Nicholls et al., 2006). A few may be synergistic with mitigation (Bosello, 2005) such as investing in more efficient buildings that will limit human vulnerability to increasingly frequent heatwaves and also reduce energy use, hence emissions. But many adaptation options involve net costs with a risk of committing to irreversible and misplaced investment given the considerable uncertainty about climate change at a local scale. Given this uncertainty, and the fact that learning about adaptation to climate change imposes some costs and takes time (Kelly et al., 2005), mis-allocation of investments may occur, or the rate of long-term investment in adaptation strategies may slow (Kokic et al., 2005; Kelly et al., 2005). Finally, the interactions between adaptation and mitigation are intertwined with development pathways. A key issue is to understand at what point (over)investment in mitigation or adaptation might limit funds available for development, and thus reduce future adaptive capacity (Sachs, 2004; Tol, 2005a; Tol and Yohe, 2006). Another issue concerns the point at which climate change damages, and the associated investment in adaptation, could crowd out more productive investments later and harm development (Kemfert, 2002; Bosello and Zhang, 2005; Kemfert and Schumacher, 2005). The answer to these questions depends upon modelling assumptions that drive repercussions in other sectors of the economy and other regions and the potential impacts on economic growth. These are ‘higher-order’ social costs of climate change from a series of climate-change-induced shocks; they include the relative influence of: a) the cross-sectoral interactions across all major sectors and regions; b) a crowding out effect that slows down capital accumulation and technical progress, especially if technical change is endogenous. These indirect impacts reduce development and adaptive capacity and may be in the same order of magnitude, or greater than, the direct impact of climate change (Fankhauser and Tol, 2005; Roson and Tol, 2006; Kemfert, 2006). Both the magnitude and the sign of the indirect macroeconomic impacts of climate change are conditional upon the growth dynamics of the countries concerned. When confronted by the same mitigation policies and the same climate change impacts, economies experiencing strong disequilibrium (including ‘poverty traps’) and large market and institutional imperfections will not react in the same way as countries that are on a steady and high economic growth pathway. The latter are near what economists call their ‘production frontier’ (the maximum of production attainable at a given point in time); the former are more vulnerable to any climatic shock or badly 226
Chapter 3
calibrated mitigation policies, but symmetrically offer more opportunities for synergies between mitigation, adaptation and development policies (Shukla et al., 2006). On the adaptation side for example, Tol and Dowlatabadi (2001) demonstrate that there is significant potential to reduce vulnerability to the spread of malaria in Africa. In some circumstances, mitigation measures can be aligned with development policies and alleviate important sources of vulnerability in these countries, such as dependency on oil imports or local pollution. But this involves transition costs over the coming 10–20 years (higher domestic energy prices, higher investments in the energy sector), which in turn suggests opportunities for international cooperative mechanisms to minimize these costs. Bosello (2005) shows complementarity between adaptation, mitigation and investment in R&D, whilst others consider these as substitutes (Tol, 2005a). Schneider and Lane (2006) consider that mitigation and adaptation only trade off for small temperature increments where adaptation might be cheaper, whereas for larger temperature increases mitigation is always the cheaper option. Goklany (2003) promotes the view that the contribution by climate change to hunger, malaria, coastal flooding, and water stress (as measured by populations at risk) is small compared to that of non-climate-change-related factors, and that through the 2080s, efforts to reduce vulnerability would be more cost-effective in reducing these problems than mitigation. This analysis neglects critical thresholds at the regional level (such as the temperature ceiling on feasibility of regional crop growth) and at the global level (such as the onset of ice sheet melting or release of methane from permafrost), and, like many others studies, it neglects the impacts of extreme weather events. It also promotes a very optimistic view of adaptive capacity, which is increasingly challenged in the literature (Tompkins and Adger, 2005). An adaptationonly policy scenario in the coming decades leads to an even greater challenge for adaptation in decades to follow, owing to the inertia of the climate system. In the absence of mitigation, temperature rises will be much greater than would otherwise occur with pusuant impacts on economic development (IPCC, 2007b, Chapter 19.3.7; Stern 2006). Hence adaptation alone is insufficient to avoid the serious risks due to climate change (see Table 3.11; also IPCC, 2007b, Chapter 19, Table 19.1). To summarize, adaptation and mitigation are thus increasingly viewed as complementary (on the global scale), whilst locally there are examples of both synergies and conflicts between the two (IPCC, 2007b, Chapter 18). Less action on mitigation raises the risk of greater climate-change-induced damages to economic development and natural systems and implies a greater need for adaptation. Some authors maintain that adaptation and mitigation are substitutes, because of competition for funds, whilst others claim that such tradeoffs occur only at the margin when considering incremental temperature change and incremental policy action, because for large temperature changes mitigation is always cheaper than adaptation.
Chapter 3
Issues related to mitigation in the long-term context
Table 3.9: Global mean temperature increase at equilibrium, greenhouse gas concentration and radiative forcing. Equilibrium temperatures here are calculated using estimates of climate sensitivity and do not take into account the full range of bio-geophysical feedbacks that may occur.
CO2-eq concentration and radiative forcing corresponding to best estimate of climate sensitivity for warming level in column 11,2 CO2-equivalent (ppm)
Radiative forcing (W/m2)
CO2-eq concentration that would be expected to limit warming below level in column 1 with an estimated likelihood of about 80% 3
0.6
319
0.7
305
1.6
402
2.0
356
2.0
441
2.5
378
2.6
507
3.2
415
3.0
556
3.7
441
3.6
639
4.5
484
4.0
701
4.9
515
4.6
805
5.7
565
5.0
883
6.2
601
5.6
1014
6.9
659
6.0
1112
7.4
701
6.6
1277
8.2
768
Equilibrium temperature increase in ºC above preindustrial temperature
Note: see Figure 3.38 on page 228 for footnotes.
3.5.2
Linking emission scenarios to changes in global mean temperature, impacts and key vulnerabilities
In a risk-management framework, a first step to understanding the environmental consequences of mitigation strategies is to look at links between various stabilization levels for concentrations of greenhouse gases in the atmosphere, and the global mean temperature change relative to a particular baseline. A second step is to link levels of temperature change and key vulnerabilities. Climate models indicate significant uncertainty at both levels. Figure 3.38 shows CO2-eq concentrations that would limit warming at equilibrium below the temperatures indicated above pre-industrial levels, for ‘best estimate’ climate sensitivity, and for the likely range of climate sensitivity (see Meehl et al., 2007, Section 10.7, and Table 10.8; and the notes to Figure 3.38). It also shows the corresponding radiative forcing levels and their relationship to equilibrium temperature and CO2-eq concentrations. The table and the figure illustrate how lower temperature constraints require lower stabilization levels, and also that, if the potential for climate sensitivities is higher than the ‘best estimate’ and is taken into account, the constraint becomes more stringent. These more stringent constraints lower the risks of exceeding the threshold. Figure 3.38 and Table 3.10 provide an overview of how emission scenarios (Section 3.3) relate to different stabilization targets and to the likelihood of staying below certain equilibrium warming levels. For example, respecting constraints of 2°C above pre-industrial levels, at equilibrium, is already outside the range of scenarios considered in this chapter, if the higher values of likely climate sensitivity are taken into account (red curve in Figure 3.38), whilst a constraint of respecting 3°C
above pre-industrial levels implies the most stringent of the category I scenarios, with emissions peaking in no more than the next 10 years, again if the higher likely values of climate sensitivity are taken into account. Using the ‘best estimate’ of climate sensitivity (i.e. the estimated mode) as a guide for establishing targets, implies the need for less stringent emission constraints. This ‘best estimate’ assumption shows that the most stringent (category I) scenarios could limit global mean temperature increases to 2°C–2.4°C above pre-industrial levels, at equilibrium, requiring emissions to peak within 10 years. Similarly, limiting temperature increases to 2°C above preindustrial levels can only be reached at the lowest end of the concentration interval found in the scenarios of category I (i.e. about 450 ppmv CO2-eq using ‘best estimate’ assumptions). By comparison, using the same ‘best estimate’ assumptions, category II scenarios could limit the increase to 2.8°C–3.2°C above pre-industrial levels at equilibrium, requiring emissions to peak within the next 25 years, whilst category IV scenarios could limit the increase to 3.2°C–4°C above pre-industrial at equilibrium requiring emissions to peak within the next 55 years. Note that Table 3.10 category IV scenarios could result in temperature increases as high as 6.1°C above pre-industrial levels, when the likely range for the value of climate sensitivity is taken into account. Hence, setting policy on the basis of a ‘best estimate’ climate sensitivity accepts a significant risk of exceeding the temperature thresholds, since the climate sensitivity could be higher than the best estimate. Table 3.11 highlights a number of climate change impacts and key vulnerabilities organized as a function of global mean temperature rise (IPCC, 2007b, Chapter 19). The table highlights a selection of key vulnerabilities representative of categories covered in Chapter 19 (Table 19.1) in IPCC (2007b). 227
Issues related to mitigation in the long-term context
Chapter 3
Equilibrium global mean temperature increase above pre-industrial (°C) 10 8 VI
6
V IV
4 I
II
III
2 0 300
400 500 600 700 800 GHG concentration stabilization level (ppm CO2 eq)
900
1000
Figure 3.38: Relationship between global mean equilibrium temperature change and stabilization concentration of greenhouse gases using: (i) ‘best estimate’ climate sensitivity of 3°C (black), (ii) upper boundary of likely range of climate sensitivity of 4.5°C (red), (iii) lower boundary of likely range of climate sensitivity of 2°C (blue) (see also Table 3.9). Notes: 1. IPCC (2007a) finds that the climate sensitivity is likely to be in the range 2°C –4.5°C, with a ‘best estimate’ of about 3°C, very unlikely to be less than 1.5°C and values substantially higher than 4.5°C ‘cannot be excluded’ (IPCC (2007a, SPM). 2. The simple relationship Teq = T2xCO2 x ln([CO2]/280)/ln(2) is used (see Meehl et al. (2007), Section 10.7, and Table 10.8), with upper and lower values of T2xCO2 of 2 and 4.5°C. 3. Non-linearities in the feedbacks (including e.g. ice cover and carbon cycle) may cause time dependence of the effective climate sensitivity, as well as leading to larger uncertainties for greater warming levels. This likelihood level is consistent with the IPCC Working Group I assessment of climate sensitivity, see Note 1, and drawn from additional consideration of Box 10.2, Figure 2, in IPCC (2007a).
The italic text in Table 3.11 highlights examples of avoided impacts derived from ensuring that temperatures are constrained to any particular temperature range compared to a higher one. For example, significant benefits result from constraining temperature change to not more than 1.6°C–2.6°C above pre-industrial levels. These benefits would include lowering (with different levels of confidence) the risk of: widespread deglaciation of the Greenland Ice Sheet; avoiding large-scale transformation of ecosystems and degradation of coral reefs; preventing terrestrial vegetation becoming a carbon source; constraining species extinction to between 10–40%; preserving many unique habitats (see IPCC, 2007b, Chapter 4, Table 4.1 and Figure 4.5) including much of the Arctic; reducing increases in flooding, drought, and fire; reducing water quality declines, and preventing global net declines in food production. Other benefits of this constraint, not shown in the Table 3.11, include reducing the risks of extreme weather events, and of at least partial deglaciation of the West Antarctic Ice Sheet (WAIS), see also IPCC, 2007b, Section 19.3.7. By comparison, for ‘best guess’ climate sensitivity, attaining these benefits becomes unlikely if emission reductions are postponed beyond the next 15 years to a time period between the next 15–55 years. Such postponement also results in increasing risks of a breakdown of the Meridional Overturning Circulation (IPCC, 2007b, Table 19.1). Even for a 2.6°C –3.6°C temperature rise above pre-industrial levels there is also medium confidence in net negative impacts in many developed countries (IPCC, 2007b, Section 19.3.7). For emission-reduction scenarios resulting in likely temperature 228
increases in excess of 3.6°C above pre-industrial levels, successively more severe impacts result. Low temperature constraints are necessary to avoid significant increases in the impacts in less developed regions of the world and in polar regions, since many market sectors in developing countries are already affected below 2.6°C above pre-industrial levels (IPCC, 2007b, Section 19.3.7), and indigenous populations in high latitude areas already face significant adverse impacts. It is possible to use stablization metrics (i.e. global mean temperature increase, concentrations in ppmv CO2-eq or radiative forcing in W/m2) in combination with the mitigation scenarios literature to assess the cost of alternative mitigation pathways that respect a given equilibrium temperature, key vulnerability (KV) or impact threshold. Whatever the target, both early and delayed-action mitigation pathways are possible, including ‘overshoot’ pathways that temporarily exceed this level. A delayed mitigation response leads to lower discounted costs of mitigation, but accelerates the rate of change and the risk of transiently overshooting pre-determined targets (IPCC, 2007b, Section 19.4.2). A strict comparison between mitigation scenarios and KVs is not feasible as the KVs in Table 3.11 refer to realized transient temperatures in the 21st century rather than equilibrium temperatures, but a less rigorous comparison is still useful. Avoidance of many KVs requires temperature change in 2100 to be below 2°C above 1990 levels (or 2.6°C above pre-industrial levels). Using equilibrium temperature as a guide, impacts or KV could be less than expected, for example if impacts
Chapter 3
Issues related to mitigation in the long-term context
Table 3.10: Properties of emissions pathways for alternative ranges of CO2 and CO2-eq stabilization targets. Post-TAR stabilization scenarios in the scenario database (see also Sections 3.2 and 3.3); data source: after Nakicenovic et al., 2006 and Hanaoka et al., 2006)
Class I
Stabilization Global mean Likely range of Anthropogenic level for temperature C global mean addition to CO2 only, increase above temperature radiative Multi-gas consistent Number pre-industrial at C increase forcing at concentration with multi-gas of equilibrium, using best above prestabilization level (ppmv level (ppmv scenario estimate of climate industrial at (W/m2) CO2-eq) CO2) studies sensitivityc) equilibriuma) 2.5-3.0 445-490 350-400 6 2.0-2.4 1.4-3.6
Peaking year for CO2 emissionsb) 2000-2015
Change in global emissions in 2050 (% of 2000 emissions)b) -85 to -50
II III
3.0-3.5 3.5-4.0
490-535 535-590
400-440 440-485
18 21
2.4-2.8 2.8-3.2
1.6-4.2 1.9-4.9
2000-2020 2010-2030
-60 to -30 -30 to +5
IV V VI
4.0-5.0 5.0-6.0 6.0-7.5
590-710 710-855 855-1130
485-570 570-660 660-790
118 9 5
3.2-4.0 4.0-4.9 4.9-6.1
2.2-6.1 2.7-7.3 3.2-8.5
2020-2060 2050-2080 2060-2090
+10 to +60 +25 to +85 +90 to +140
Notes: a. Warming for each stabilization class is calculated based on the variation of climate sensitivity between 2ºC –4.5ºC, which corresponds to the likely range of climate sensitivity as defined by Meehl et al. (2007,Chapter 10). b. Ranges correspond to the 70% percentile of the post-TAR scenario distribution. c. ‘Best estimate’ refers to the most likely value of climate sensitivity, i.e. the mode (see Meehl et al. (2007,Chapter 10) and Table 3.9
do not occur until the 22nd century, because there is more time for adaptation. Or they might be greater than expected, as temperatures in the 21st century may transiently overshoot the equilibrium, or stocks at risk (such as human populations) might be larger. Some studies explore the link between transient and equilibrium temperature change for alternative emission pathways (O’Neill and Oppenheimer, 2004; Schneider and Mastrandrea, 2005; Meinshausen, 2006). It is transient climate change, rather than equilibrium change, that will drive impacts. More research is required to address the question of emission pathways and transient climate changes and their links to impacts.25 In the meantime, equilibrium temperature change may be interpreted as a gross indicator of change, and given the caveats above, as a rough guide for policymakers’ consideration of KV and mitigation options to avoid KV. 3.5.3
Information for integrated assessment of response strategies
Based upon a better understanding of the links between concentration levels, magnitude and rate of warming and key vulnerabilities, the next step in integrated assessment is to make informed decisions by combining information on climate science, impact analysis and economic analysis within a consistent analytical framework. These exercises can be grouped into three main categories depending on the way uncertainty is dealt with, the degree of complexity and multidisciplinary nature of models and on the degree of ambition in terms of normative insights: 1. Assessment and sensitivity analysis of climate targets. 2. Inverse analyses to determine emission-reduction corridors (trajectories) to avoid certain levels of climate change or of climate impacts.
3. Monetary assessment of climate change damages. Section 3.6 discusses how this information is used in economic analyses to determine optimal emission pathways. 3.5.3.1
Scenario and sensitivity analysis of climate targets
Probabilistic scenario analysis can be used to assess the risk of overshooting some climate target or to produce probabilistic projections that quantify the likelihood of a particular outcome. Targets for such analysis can be expressed in several different ways: absolute global mean temperature rise by 2100, rate of climate change, other thresholds beyond which dangerous anthropogenic interference (DAI) may occur, or additional numbers of people at risk to various stresses. For example, Arnell et al. (2002) show that such stresses (conversion of forests to grasslands, coastal flood risk, water stress) are far less at 550 ppmv than at 750 ppmv. Recent Integrated Assessment Models (IAM) literature reflects a renewed attention to climate sensitivity as a key driver of climate dynamics (Den Elzen and Meinshausen, 2006; Hare and Meinshausen, 2006; Harvey, 2006; Keller et al., 2006; Mastrandrea and Schneider, 2004; Meehl et al., 2005; Meinshausen et al., 2006, Meinshausen, 2006; O’Neill and Oppeinheimer, 2002, 2004; Schneider and Lane, 2004; Wigley, 2005). The consideration of a full range of possible climate sensitivity increases the probability of exceeding thresholds for specific DAI. It also magnifies the consequence of delaying mitigation efforts. Hare and Meinshausen (2006) estimate that each 10-year delay in mitigation implies an additional 0.2°C–0.3°C warming over a 100–400 year time horizon. For a climate sensitivity of 3°C, Harvey (2006) shows that immediate mitigation is required to constrain temperature rise to roughly
25 See IPCC (2007b, Section 19.4, Figure 19.2) and Meehl et al. (2007, Section 10.7) for further discussion of equilibrium and transient temperature increases in relation to stabilization pathways
229
230
Near-total deglaciation**
Commitment to widespread** to near-total deglaciation* 2-7 m sea level rise over centuries to millennia
Lowers risk of near-total deglaciation
Localized deglaciation (already observed due to local warming), extent would increase with temperature**
Lowers risk of widespread** to near-total deglaciation*
GMT range relative to 1990 (preindustrial)
>4 (>4-6)
3-4 (3.6-4.6)
2-3 (2.6-3.6)
1-2 (1.6-2.6)
0-1 (0.6-1.6)
Reduces extinctions to below 10-30%*; reduces disturbance levels***
10-40% of species committed to extinction* Reduces extinctions to below 20-50%*, prevents vegetation becoming carbon source*/** Many ecosystems already affected***
Widespread disturbance, sensitive to rate of climate change and land use*** 20 to 50% species committed to extinction* Avoids widespread disturbance to ecosystems and their services***, and constrains species losses
Global vegetation becomes net source of C above 2-3ºC */**
Large-scale transformation of ecosystems and ecosystem services** At least 35% of species committed to extinction (3°C)**
Global biological systems Example: terrestrial ecosystemsb (IPCC, 2007b: 4.4.11; 1.3.4; 1.3.5)
Increased flooding and drought severity** Lowers risk of floods, droughts, deteriorating water quality*** and reduced water supplied for hundreds of millions of people**
Hundreds of millions people would face reduced water supplies (**)
Sea level rise will extend areas of salinization of ground water, decreasing freshwater availability in coastal areas***
Severity of floods, droughts, erosion, water quality deterioration will increase with increasing climate change***
Global social systems Example: waterc (IPCC, 2007b: 3 ES; 3.4.3; 13.4.3)
Increased global production o/* Lowers risk of decrease in global food production and reduces regional losses (or gains) o/*
Reduced low latitude production*. Increased high latitude production* (1-3ºC)
Global food production peaks and begins to decrease o/* (1-3ºC) Lowers risk of further declines in global food production associated with higher temperatures*
Further declines in global food production o/*
Global social systems Example: food supplyc (IPCC, 2007b: 5.6.1; 5.6.4)
Reduced loss of ice cover and permafrost; limits risk to Arctic ecosystems and limits disruption of traditional ways of life**
Climate change is already having substantial impacts on societal and ecological systems***
While some economic opportunities will open up (e.g. shipping), traditional ways of life will be disrupted**
Continued warming likely to lead to further loss of ice cover and permafrost**. Arctic ecosystems further threatened**, although net ecosystem productivity estimated to increase (o)
Regional systems Example: Polar Regionsd (IPCC, 2007b: 15.4.1; 15.4.2; 15.4.6; 15.4.7)
Lowers risk of more frequent and more intense fires in many areas**
Increased fire frequency and intensity in many areas, particularly where drought increases**
Frequency and intensity likely to be greater, especially in boreal forests and dry peat lands after melting of permafrost**
Extreme events Example: fire riske (IPCC, 2007a: 7.3; IPCC, 2007b; 1.3.6)
Notes: Plain text shows predicted vulnerabilities in various temperature ranges for global annual mean temperature rise relative to 1990. Italic text shows benefits (or damage avoided) upon constraining temperature increase to lower compared to higher temperature ranges. Confidence symbol legend: o low confidence; * medium confidence; ** high confidence; *** very high confidence Excerpts from IPCC, 2007b, Table 19.1; a. Refer to IPCC (2007b, Table 19.1) for further information, also concerning bio-geochemical cycles, West Antarctic Ice Sheet and Meridional Overturning Circulation b. Refer to IPCC (2007b, Table 19.1) for further information, also concerning marine and freshwater ecosystems c. Refer to IPCC (2007b, Table 19.1) for further information, also concerning infrastructure, health, migration and conflict, and aggregate market impacts d. Refer to IPCC (2007b, Table 19.1) for further information and also for other regions e. Refer to IPCC (2007b, Table 19.1) for further information, also concerning tropical cyclones, flooding, extreme heat, and drought
Geophysical systems Example: Greenland ice sheeta (IPCC, 2007b: 6.3; 19.3.5.2; IPCC, 2007a: 4.7.4; 6.4.3.3; 10.7.4.3; 10.7.4.4)
Table 3.11: Examples of key vulnerabilities (taken from IPCC, 2007b, Table 19.1).
Issues related to mitigation in the long-term context Chapter 3
Chapter 3
Issues related to mitigation in the long-term context
2°C above pre-industrial levels. Only in the unlikely situation where climate sensitivity is 1°C or lower would immediate mitigation not be necessary.26 Harvey also points out that, even in the case of a 2°C threshold (above pre-industrial levels), acidification of the ocean would still occur and that this might not be considered safe. Another focus of sensitivity analysis is on mitigation scenarios that overshoot and eventually return to a given stabilization or temperature target (Kheshgi, 2004; Wigley, 2005; Harvey, 2004; Izrael and Semenov, 2005; Kheshgi et al., 2005; Meinshausen et al., 2006). Schneider and Mastrandrea (2005) find that this risk of exceeding a threshold of 2ºC above pre-industrial levels is increased by 70% for an overshoot scenario stabilizing at 500 ppmv CO2-eq (as compared to a scenario stabilizing at 500 ppmv CO2-eq). Such overshoot scenarios are likely to be necessary if there is a decision to achieve stablization of GHG concentrations close to (or at) today’s levels. They are indeed likely to lower the costs of mitigation but, in turn, raise the risk of exceeding such thresholds (Keller et al., 2006; Schneider and Lane, 2004) and may limit the ability to adapt by increasing the rate of climate change, at least temporarily (Hare and Meinshausen, 2006). O’Neill and Oppenheimer (2004) find that the transient temperature up to 2100 is equally, or more, controlled by the pathway to stabilization than by the stabilization target, and that overshooting can lead to a peak temperature increase that is higher than in the long-term (equilibrium) warming. The last and important contribution of this approach is to test the sensitivity of results to carbon cycle and climate change feedbacks (Cox et al., 2000; Friedlingstein et al., 2001; Matthews, 2005) and other factors that may affect carbon cycle dynamics, such as deforestation (Gitz and Ciais, 2003). For example, carbon cycle feedbacks amplify warming (Meehl et al., 2007) and are omitted from most other studies that thus underestimate the risks of exceeding (or overshooting) temperature targets for a given effort of mitigation in the energy sector only. This could increase warming by up to 1°C in 2100, according to a simple model (Meehl et al., 2007). The amplification, together with further potential amplification due to feedbacks of uncertain magnitude, such as the potential release of methane from permafrost, peat bogs and seafloor clathrates (Meehl et al., 2007) are also not included in the analysis presented in Figure 3.38 and Table 3.10. This analysis reflects only known feedbacks for which the magnitude can be estimated and are included in General Circulation Models (GCMs). Hence, scenario and sensitivity analysis shows that the risks of exceeding a given temperature threshold for a given temperature target may be higher than that shown in Table 3.10 and Figure 3.38. 3.5.3.2
Inverse modelling and guardrail analysis
Inverse modelling approaches such as Safe Landing Analysis (Swart et al., 1998) and Tolerable Windows Approach (Toth,
2003), aim to define a guardrail of allowable emissions for sets of unacceptable impacts or intolerable mitigation costs. They explore how the set of viable emissions pathways is constrained by parameters such as the starting date, the rate of emission reductions, or the environmental constraints. They provide insights into the influence of short-term decisions on longterm targets by delineating allowable emissions corridor, but they do not prescribe unique emissions pathways, as per costeffectiveness or costs-benefit analysis. For example, Toth et al. (2002) draw on climate impact response functions (CIRFs) by Füssel and van Minnen (2001) that use detailed biophysical models to estimate regionally specific, non-monetized impacts for different sectors (i.e. agricultural production, forestry, water runoff and biome changes). They show that the business-as-usual scenario of GHG emissions (which resembles the SRES A2 scenario) to 2040 precludes the possibility of limiting the worldwide transformation of ecosystems to 30% or less, even with very high willingness to pay for the mitigation of GHG emissions afterwards. Some applications of guardrail analyses assess the relationship between emission pathways and abrupt change such as thermohaline circulation (THC) collapse (Rahmstorf and Zickfeld, 2005). The latter study concludes that stringent mitigation policy reduces the probability of THC collapse but cannot entirely avoid the risk of shutdown. Corfee-Morlot and Höhne (2003) conclude that only low stabilization targets (e.g. 450 ppmv CO2 or 550 ppmv CO2-eq) significantly reduce the likelihood of climate change impacts. They use an inverse analysis to conclude that more than half of the SRES (baseline) emission scenarios leave this objective virtually out of reach as of 2020. More generally, referring to Table 3.10, if the peaking of global emissions is postponed beyond the next 15 years to a time period somewhere between the next 15–55 years, then constraining global temperature rise to below 2°C above 1990 (2.6°C above pre-industrial levels) becomes unlikely (using ‘best estimate’ assumptions of climate sensitivity), resulting in increased risks of the impacts listed in Table 3.11 and discussed in Section 3.5.2. 3.5.3.3
Cost-benefit analysis, damage cost estimates and social costs of carbon
The above analysis provides a means of eliminating those emissions scenarios that are outside sets of pre-determined guardrails for climate protection and provides the raw material for cost-effectiveness analysis of optimal pathways for GHG emissions. If one wants to determine these pathways through a cost-benefit analysis it is necessary to assess the trade-off between mitigation, adaptation and damages, and consequently, to measure damages in the same monetary metric as mitigation
26 This is below the range accepted by IPCC Working Group I.
231
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Some argue that it is necessary to specify more precisely why certain impacts are undesirable and to comprehensively itemize the economic consequences of climate change in monetary terms. The credibility of such efforts has often been questioned, given the uncertainty surrounding climate impacts and the efficacy of societal responses to them, plus the controversial meaning of a monetary metric across different regions and generations (Jacoby, 2004). This explains why few economists have taken the step of monetizing global climate impacts. At the time of the TAR, only three such comprehensive studies had been published (Mendelsohn et al., 2000; Nordhaus and Boyer, 2000; and Tol, 2002a, 2002b). Their estimates ranged from negligible to 1.5% of the GDP for a global mean temperature rise of +2.5°C and Nordhaus and Boyer carefully warned: ‘Along the economically efficient emission path, the longrun global average temperature after 500 years is projected to increase 6.2°C over the 1900 global climate. While we have only the foggiest idea of what this would imply in terms of ecological, economic, and social outcomes, it would make the most thoughtful people, even economists, nervous to induce such a large environmental change. Given the potential for unintended and potentially disastrous consequences….’ Progress has been made since the TAR in assessing the impacts of climate change. Nonetheless, as noted in Watkiss et al. (2005), estimates of the social costs of carbon (SCC) in the recent literature still reflect an incomplete subset of relevant impacts; many significant impacts have not yet been monetized (see also IPCC, 2007b; for SCC see IPCC (2007b, Section 20.6) and others are calibrated in numeraires that may defy monetization for some time to come. Existing reviews of available SCC estimates show that they span several orders of magnitude – ranges that reflect uncertainties in climate sensitivity, response lags, discount rates, the treatment of equity, the valuation of economic and non-economic impacts, and the treatment of possible catastrophic losses (IPCC, 2007b, Chapter 20). The majority of available estimates in the literature also capture only impacts driven by lower levels of climate change (e.g. 3°C above 1990 levels). IPCC (2007b) highlights available estimates of SCC that run from -3 to 95 US$ /tCO2 from one survey, but also note that another survey includes a few estimates as high as 400 US$/tCO2 (IPCC, 2007b, Chapter 20, ES and Section 20.6.1). However the lower boundary of this range includes studies where climate change is presumed to be low and aggregate benefits accrue. Moreover, none of the aggregate estimates reflect the significant differences in impacts that will be felt across different regions; nor do they capture any of the social costs of other greenhouse gases. A more recent estimate by Stern (2006) is at the high end of these estimates (at 85 US$/ tCO2) because an extremely low discount rate (of 1.4%) is used in calculating damages that include additional costs attributed to abrupt change and increases in global mean temperature for 232
Values increase with Aggregation method changing from output weighted.... Social cost of carbon: range of values
and adaptation expenditures. Such assessment can be carried out directly in the form of ‘willingness to pay for’ avoiding certain physical consequences.
Chapter 3
Factors that decrease SCC: Low climate sensitivity High adaptive capacity Perfect foresight Omission of abrupt change Short-lived damages Low value of life Low ecosystem value Limited impact coverage Direct costs only Limited geographic detail
.....to equity weighted
Factors that increase SCC: High climate sensitivity Low adaptive capacity Imperfect foresight Coverage of abrupt change Enduring damages High value of life High ecosystem value Comprehensive impacts Indirect & direct costs High geographic detail
Values increase with decreasing discount rate
Figure 3.39: Factors influencing the social costs of carbon. Source: Downing et al., 2005
some scenarios in excess of 7°C (Nordhaus, 2006a; Yohe, 2006; Tol and Yohe, 2006). The long-term high-temperature scenarios are due to inclusion of feedback processes. IPCC (2007b) also highlights the fact that the social costs of carbon and other greenhouse gases could increase over time by 2–4% per year (IPCC, 2007b; Chapter 20, ES and Section 20.6.1). For a given level of climate change, the discrepancies in estimates of the social costs of carbon can be explained by a number of parameters highlighted in Figure 3.39. These stem from two different types of questions: normative and empirical. Key normative parameters include the inter-temporal aggregation of damages through discount rates and aggregation methods for impacts across diverse populations within the same time period (Azar and Lindgren, 2003; Howarth, 2003; Mastrandrea and Schneider, 2004) and are responsible for much of the variation. The other parameters relate to the empirical validity of their assessment, given the poor quality of data and the difficulty of predicting how society will react to climate impacts in a given sector, at a given scale in future decades. Pearce (2003) suggests that climate damages and SCC may be over-estimated due to the omission of possible amenity benefits in warmer climates or high-latitude regions (Maddison 2001) and possible agricultural benefits. However, overall, it is likely that current SCC estimates are understated due to the omission of significant impacts that have not yet been monetized (IPCC, 2007b, Chapters 19 and 20; Watkiss et al., 2005). Key empirical parameters that increase the social value of damages include: • Climate sensitivity and response lag. Equilibrium temperature rise for a doubling of CO2, and the modelled response time of climate to such a change in forcing. Hope (2006) in his PAGE 2002 model found that, as climate sensitivity was varied from 1.5°–5°C, the model identified a strong correlation with SCC.
Chapter 3
• Coverage of abrupt or catastrophic changes, such as the crossing of the THC threshold (Keller et al., 2000 and 2004; Mastrandrea and Schneider, 2001; Hall and Behl, 2006) or the release of methane from permafrost and the weakening of carbon sinks. The Stern Review (2006) finds that such abrupt changes may more than double the market damages (e.g. from 2.1% to 5% of global GDP) if temperatures were to rise by 7.4°C in 2200. • Inclusion and social value of non-market impacts: what value will future generations place on impacts, such as the quality of landscape or biodiversity? • Valuation methods for market impacts such as the value of life. • Adaptative capacity: social costs will be magnified if climate change impacts fall on fragile economies. • Predictive capacity: studies finding efficient adaptation assume that actors decide using perfect foresight (after a learning process; see Mendelsohn and Williams, 2004). Higher costs are found if one considers the volatility of climate signals and transaction costs. For agriculture, Parry et al. (2004) shows the costs of a mismatch between expectations and real climate change (sunk costs, value of real estates, and of capital stock). • Geographic downscaling: using a geographic-economic cross-sectional (1990) database, Nordhaus (2006a) concludes that this downscaling leads to increased damage costs, from previous 0.7% estimates to 3% of world output for a 3°C increase in global mean temperature. • The propagation of local economic and social shocks: this blurs the distinction between winners and losers. The magnitude of this type of indirect impact depends on the existence of compensation mechanisms, including direct assistance and insurance as well as on how the crosssectoral interdependences and transition costs are captured by models (see Section 3.5.1). The influence of this set of parameters, which is set differently in various studies, explains the wide range of estimates for the SCC. In an economically-efficient mitigation response, the marginal costs of mitigation should be equated to the marginal benefits of emission reduction. The marginal benefits are the avoided damages for an additional tonne of carbon abated within a given emission pathway, also known as the SCC. As discussed in Section 3.6, both sides of this equation are uncertain, which is why a sequential or iterative decision-making framework, with progressive resolution of information, is needed. Despite a paucity of analytical results in this area, it is possible to draw on today’s literature to make a first comparison between the range of SCC estimates and the range of marginal costs of mitigation across different scenarios. IPCC (2007b, Chapter 20) reviews ranges of SCC from available literature. Allowing for a range of SCC between 4–95 US$/tCO2 (14–350 US$/tC from Tol (2005b) median and 95th percentile estimates) and assuming a 2.4% per year increase (IPCC, 2007b, Chapter 20), produces a
Issues related to mitigation in the long-term context
range of estimates for 2030 of 8–189 US$/tCO2. The mitigation studies in this chapter suggest carbon prices in 2030 of 1–24 US$/tCO2-eq for category IV scenarios, 18–79 US$/tCO2-eq for category III scenarios, and 31–121 US$/tCO2-eq for category I and II scenarios (see Sections 3.3 and 3.6).
3.6 Links between short-term emissions trends, envisaged policies and longterm climate policy targets In selecting the most appropriate portfolio of policies to deal with climate change, it is important to distinguish between the case of ‘certainty’, where the ultimate target is known from the outset, and a ‘probabilistic’ case, where there is uncertainty about the level of a ‘dangerous interference’ and about the costs of greenhouse gas abatement. In the case of certainty, the choice of emissions pathway can be seen as a pure GHG budget problem, depending on a host of parameters (discounting, technical change, socio-economic inertia, carbon cycle and climate dynamics, to name the most critical) that shape its allocation across time. The IPCC Second and Third Assessment Reports demonstrated why this approach is an oversimplification and therefore misleading. Policymakers are not required to make once-and-for-all decisions, binding their successors over very long time horizons, and there will be ample opportunities for mid-course adjustments in the light of new information. The choice of short-term abatement rate (and adaptation strategies) involves balancing the economic risks of rapid abatement now and the reshaping of the capital stock that could later be proven unnecessary, against the corresponding risks of delay. Delay may entail more drastic adaptation measures and more rapid emissions reductions later to avoid serious damages, thus necessitating premature retirement of future capital stock or taking the risk of losing the option of reaching a certain target altogether (IPCC, 1996b, SPM). The calculation of such short-term ‘optimal’ decisions in a cost-benefit framework assumes the existence of a metaphorical ‘benevolent planner’ mandated by cooperative stakeholders. The planner maximizes total welfare under given economic, technical and climate conditions, given subjective visions of climate risks and attitudes towards risks. A risk-taking society might choose to delay action and take the (small) risk of triggering significant and possibly irreversible abrupt change impacts over the long-term. If society is averse to risk – that is, interested in avoiding worst-case outcomes – it would prefer hedging behaviour, implying more intense and earlier mitigation efforts. A significant amount of material has been produced since the SAR and the TAR to upgrade our understanding of the parameters influencing the decisions about the appropriate timing of climate action in a hedging perspective. We review 233
Issues related to mitigation in the long-term context
these recent developments, starting with insights from a body of literature drawing on analytical models or compact IAMs. We then assess the findings from the literature for short-term sectoral emission and mitigation estimates from top-down economy-wide models. 3.6.1
Insights into the choice of a short-term hedging strategy in the context of long-term uncertainty
There are two main ways of framing the decision-making approaches for addressing the climate change mitigation and adaptation strategies. They depend on different metrics used to assess the benefits of climate policies: a. A cost-effectiveness analysis that minimizes the discounted costs of meeting various climate constraints (concentration ceiling, temperature targets, rate of global warming). b. A cost-benefit analysis that employs monetary estimates of the damages caused by climate change and finds the optimal emissions pathway by minimizing the discounted present value of adaptation and mitigation costs, co-benefits and residual damages. The choice between indicators of the mitigation benefits reflects a judgment on the quality of the available information and its ability to serve as a common basis in the decision-making process. Actually the necessary time to obtain comprehensive, non-controversial estimates of climate policy benefits imposes a trade-off between the measurement accuracy of indicators describing the benefits of climate policies (which diminishes as one moves down the causal chain from global warming to impacts and as one downscales simulation results) and their relevance, that is their capacity to translate information that policymakers may desire, ideally prior to a fully-informed decision. Using a set of environmental constraints is simply a way of considering that, beyond such constraints, the threat of climate change might become unacceptable; in a monetarymetric, or valuation approach, the same expectation can be translated through using damage curves with dangerous thresholds. The only serious source of divergence between the two approaches is the discount rate. Within a cost-effectiveness framework, environmental constraints are not influenced by discounting. Conversely, in a cost-benefit framework, some benefits occur later than costs and thus have a lower weighting when discounted. 3.6.1.1
Influence of passing from concentration targets to temperature targets in a cost-effectiveness framework
New studies such as Den Elzen et al. (2006) confirm previous results. They establish that reaching a concentration target as low as 450 ppmv CO2-eq, under even optimistic assumptions of full participation, poses significant challenges in the 2030–2040 timeframe, with rapidly increasing emission reduction rates and rising costs. In a stochastic cost-effectiveness framework, 234
Chapter 3
reaching such targets requires a significant and early emissions reduction with respect to respective baselines. But concentration ceilings are a poor surrogate for climate change risks: they bypass many links from atmospheric chemistry to ultimate damages and they only refer to longterm implications of global warming. A better proxy of climate change impacts can be found in global mean temperature: every regional assessment of climate change impacts refers to this parameter, making it easier for stakeholders to grasp the stakes of global warming for their region; one can also take into account the rate of climate change, a major determinant of impacts and damages. Therefore, with a noticeable acceleration in the last few years, the scientific community has concentrated on assessing climate policies in the context of climate stabilization around various temperature targets. These contributions have mainly examined the influence of the uncertainty about climate sensitivity on the allowable (short-term) GHGs emissions budget and on the corresponding stringency of the climatic constraints, either through sensitivity analyses (Böhringer et al., 2006; Caldeira et al., 2003; Den Elzen and Meinshausen, 2006; Richels et al., 2004) or within an optimal control frame-work (Ambrosi et al., 2003; Yohe et al., 2004). On the whole, these studies reach similar conclusions, outlining the significance of uncertainty about climate sensitivity. Ambrosi et al. (2003) demonstrates the information value of climate sensitivity before 2030, given the significant economic regrets from a precautionary climate policy in the presence of uncertainty about this parameter. Such information might not be available soon (i.e. at least 50 years could be necessary – Kelly et al., 2000). Yohe et al. (2004) thus conclude: ‘uncertainty (about climate sensitivity) is the reason for acting in the near term and uncertainty cannot be used as a justification for doing nothing’. A few authors analyze the trade-off between a costly acceleration of mitigation costs and a (temporary) overshoot of targets, and the climate impacts of this overshoot. Ambrosi et al. (2003) did so through a willingness to pay for not interfering with the climate system. They show that allowing for overshoot of an ex-ante target significantly decreases the required acceleration of decarbonization and the peak of abatement costs, but does not drastically change the level of abatement in the first period. However, the overshoot may significantly increase climate change damages as discussed above (see Section 3.5). Another result is that higher climate sensitivity magnifies the rate of warming, which in turn exacerbates adaptation difficulties, and leads to stringent abatement policy recommendations for the coming decades (Ambrosi, 2007). This result is robust for the choice of discount rate; uncertainty about the rate constraint is proven to be more important for short-term decisions than uncertainty about the magnitude of warming. Therefore, research should be aimed at better characterizing early climate
Chapter 3
Issues related to mitigation in the long-term context
change risks with a view to helping decision-makers in agreeing on a safe guardrail to limit the rate of global warming.
example, one challenge is to avoid further build-up of carbonintensive capital stock.
3.6.1.2
3.6.2
Implications of assumptions concerning damage functions in cost-benefit analysis
What is remarkable in cost-benefit studies of the optimal timing of mitigation is that the shape (or curvature) of the damage function matters even more than the ultimate level of damages – a fact long established by Peck and Teisberg (1995). With damage functions exhibiting smooth and regular damages (such as power functions with integer exponents or polynomial functions), GHG abatement is postponed. This is because, for several decades, the temporal rate of increase in marginal climate change damage remains low enough to conclude that investments to accelerate the rate of economic growth are more socially profitable that investing in abatement. This result changes if singularities in the damage curve represent non-linear events. Including even small probabilities of catastrophic ‘nasty surprises’ may substantially alter optimal short-term carbon taxes (Mastrandea and Schneider, 2004; Azar and Lindgren, 2003). Many other authors report similar findings (Azar and Schneider, 2001; Howarth, 2003; Dumas and Ha-Duong, 2005; Baranzini et al., 2003), whilst Hall and Behl (2006) suggest a damage function reflecting climate instability needs to include discontinuities in capital stock and the rate of return on capital, and hysteresis with respect to heating and cooling – resulting in a non-convex optimization function such that economic optimization models can provide no solution. But these surprises may be caused by forces other than large catastrophic events. They may also be triggered by smooth climate changes that exceed a vulnerability threshold (e.g. shocks to agricultural systems in developing countries leading to starvation) or by policies that lead to maladaptations to climate change. In the case of an irreversible THC collapse, Keller et al. (2004) point out another seemingly paradoxical result: if a climate catastrophe seems very likely within a short-term time horizon, it might be economically sound to accept its consequences instead of investing in expensive mitigation to avoid the inevitable. This shows that temporary overshoot of a pre-determined target may be preferable to bearing the social costs of an exaggerated reduction in emission, as well as the need to be attentive to ‘windows of opportunity’ for abatement action. The converse argument is that timely abatement measures, especially in the case of ITC, can reduce long-term mitigation costs and avoid some of the catastrophic events. In this respect, limited differences in GMT curves for different emissions pathways within coming decades are often misinterpreted. It does not imply that early mitigation activities would make no material difference to long-term warming. On the contrary, if the social value of the damages is high enough to justify deep emission cuts decades from now, then early action is necessary due to inertia in socio-economic systems. For
3.6.2.1
Evaluation of short-term mitigation opportunities in long-term stabilization scenarios Studies reporting short-term sectoral reduction levels
While there are many potential emissions pathways to a particular stabilization target from a specific year, it is possible to define emissions trajectories based on short-term mitigation opportunities that are consistent with a given stabilization target. This section assesses scenario results (by sector) from top-down models for the year 2030, to evaluate the range of short-term mitigation opportunities in long-term stabilization scenarios. To put these identified mitigation opportunities in context, Chapter 11, Section 11.3 compares the short-term mitigation estimates across all of the economic sectors. Many of the modelling scenarios represented in this section were an outcome from the Energy Modelling Forum Study 21 (EMF-21), which focused specifically on multi-gas strategies to address climate change stabilization (see De la Chesnaye and Weyant, 2006). Models that were evaluated in this assessment are listed in Table 3.12. For each model, the resulting emissions in the mitigation case for each economic sector in 2030 were compared to projected emissions in a reference case. Results were compared across a range of stabilization targets. For more detail on the relationship between stabilization targets defined in concentrations, radiative forcing and temperature, see Section 3.3.2. Key assumptions and attributes vary across the models evaluated, thus having an impact on the results. Most of the top-down models evaluated have a time horizon beyond 2050 such as AIM, IPAC, IMAGE, GRAPE, MiniCAM, MERGE, MESSAGE, and WIAGEM. Top-down models with a time horizon up to 2050, such as POLES and SGM, were also evaluated. The models also vary in their solution concept. Some models provide a solution based on inter-temporal optimization, allowing mitigation options to be adopted with perfect foresight as to what the future carbon price will be. Other models are based on a recursive dynamic, allowing mitigation options to be adopted based only on today’s carbon price. Recursive dynamic models tend to show higher carbon prices to achieve the same emission reductions as in inter-temporal optimization models, because emitters do not have the foresight to take early mitigation actions that may have been cheaper (for more discussion on modelling approaches, refer to Section 3.3.3). Three important considerations need to be remembered with regard to the reported carbon prices. First, these mitigation scenarios assume complete ‘what’ and ‘where’ flexibility (i.e. 235
Issues related to mitigation in the long-term context
Chapter 3
Table 3.12: Top-down models assessed for mitigation opportunities in 2030
Model
Model type
Solution concept
Time horizon
Modelling team and reference
AIM (Asian-Pacific Integrated Model)
Multi-Sector General Equilibrium
Recursive Dynamic
Beyond 2050
NIES/Kyoto Univ., Japan Fujino et al., 2006.
GRAPE (Global Relationship Assessment to Protect the Environment)
Aggregate General Equilibrium
Inter-temporal Optimization
Inter-temporal Optimization
Institute for Applied Energy, Japan Kurosawa, 2006.
IMAGE (Integrated Model to Assess The Global Environment)
Market Equilibrium
Recursive Dynamic
Beyond 2050
Netherlands Env. Assessment Agency Van Vuuren et al., Energy Journal, 2006a. (IMAGE 2.2) Van Vuuren et al., Climatic Change, 2007. (IMAGE 2.3)
IPAC (Integrated Projection Assessments for China)
Multi-Sector General Equilibrium
Recursive Dynamic
Beyond 2050
Energy Research Institute, China Jiang et al., 2006.
MERGE (Model for Evaluating Regional and Global Effects of GHG Reduction Policies)
Aggregate General Equilibrium
Inter-temporal Optimization
Beyond 2050
EPRI & PNNL/Univ. Maryland, U.S. USCCSP, 2006.
MESSAGE-MACRO (Model for Energy Supply Strategy Alternatives and Their General Environmental Impact)
Hybrid: Systems Engineering & Market Equilibrium
Inter-temporal Optimization
Beyond 2050
International Institute for Applied Systems Analysis, Austria Rao and Riahi, 2006.
MiniCam (Mini-Climate Assessment Model)
Market Equilibrium
Recursive Dynamic
Beyond 2050
PNNL/Univ. Maryland, U.S. Smith and Wigley, 2006.
SGM (Second Generation Model)
Multi-Sector General Equilibrium
Recursive Dynamic
Up to 2050
PNNL/Univ. Maryland and EPA, U.S. Fawcett and Sands, 2006.
POLES (Prospective Outlook on Long-Term Energy Systems)
Market Equilibrium
Recursive Dynamic
Up to 2050
LEPII-EPE & ENERDATA, France Criqui et al., 2006.
WIAGEM (World Integrated Applied General Equilibrium Model)
Multi-Sector General Equilibrium
Inter-temporal Optimization
Beyond 2050
Humboldt University and DIW Berlin, Germany Kemfert et al., 2006.
Source: Weyant et al., 2006.
there is full substitution among GHGs and reductions take place anywhere in the world, according to the principle of least cost). Limiting the degree of flexibility in these mitigation scenarios, such as limiting mitigation only to CO2, removing major countries or regions from undertaking mitigation, or both, will increase carbon prices, all else being equal. Second, the carbon prices of realizing these levels of mitigation increase in the time horizon beyond 2030. See Figure 3.25 for an illustration of carbon prices across longer time horizons from top-down scenarios. Third, at the economic sector level, estimated emission reduction for all greenhouse gases varies significantly across the different model scenarios, in part because each model uses sector definitions specific to that type of model. Across all the models, the long-term target in the stabilization scenarios could be met through the mitigation of multiple greenhouse gases (CO2, CH4, N2O and high-GWP gases). However the specific mitigation options and the treatment of technological progress vary across the models. For example, only some of the models include carbon capture and storage as a mitigation option (GRAPE, IMAGE, IPAC, MiniCAM, 236
and MESSAGE). Some models also include forest sinks as a mitigation option. The model results shown in Table 3.13 do not include forest sinks as a mitigation option, while the results shown in Table 3.14 do include forest sinks, as described in further detail below. Table 3.13 illustrates the amount of global GHG mitigation reported by sector for the year 2030 across a range of multigas stabilization targets. Across the higher Category IV stabilization target scenarios, emission reductions of 3–31% from the reference case emissions across all greenhouse gases can be achieved for a carbon price of 2–57 US$/tCO2-eq. The results from the POLES models fall into the higher end of the price range, in part due to the recursive dynamic nature of the model, and also due to its shorter time horizon over which to plan. The results from the GRAPE model fall into the lower end of the price range, which is the only inter-temporally optimizing model shown in the higher stabilization scenarios. In the GRAPE results, only 3% of the emissions are reduced by 2030, implying that the majority of the mitigation necessary to meet the target is undertaken beyond 2030. In scenarios
Chapter 3
Issues related to mitigation in the long-term context
Table 3.13: Global emission reductions from top-down models in 2030 by sector for multi-gas scenarios.
Model
POLES
IPAC
AIM
Stabilization category
MiniCAM
SGM
MERGE
WIAGEM
Category II
Category I
550 ppmv
550 ppmv
4.5 W/m2 from preIndustrial
4.5 W/m2 from preIndustrial
4.5 W/m2 from preIndustrial
From MiniCAM trajectory
3.4 W/m2 from preIndustrial
2% from preIndustrial
57
14
29
2
12
21
192
9
53.0
55.3
49.4
57.0
54.2
53.5
47.2
43.1
Energy supply: electric
9.5
6.4
5.2
0.5
7.3
3.1
9.5
7.0
Energy supply: non-electric
3.0
0.6
1.1
0.0
1.5
1.6a
3.2
1.7
Transportation demand
0.5
0.8
0.5
0.1
0.2
0.4a
Included in Energy supply
Included in Energy supply
Buildings demand
1.0
0.6
0.5
0.4
0.3
Included in Energy supply
Included in Energy supply
Included in Energy supply
Industry demand
1.9
1.2
0.5
Included in Buildings demand
1.7
Included in Energy supply
Included in Energy supply
Included in Energy supply
Industry production
0.8
0.0
0.8
0.3h
0.2d
1.7a
3.6b
3.6
(0.2)
(1.0)e
2.0
0.6
0.3
1.7
Included in industry production
1.1
Stabilization target
Carbon price in 2030 (2000 US$/tCO2-eq) Reference emissions 2030 Total all gases (GtCO2-eq)
Sector Mitigation estimates in 2030 (total all gases GtCO2-eq)
GRAPE
Category VI
Agriculture
Forestry
No mitigation options modelled
No mitigation options modelled
Included in another sector
0.0g
Included in Buildings demand
0.0f
0.3
0.5
Included in Industry production
No mitigation options modelled
Global total
16.4
8.7
10.6
1.9
11.9
11.2a
16.3
15.5c
Mitigation as % of reference emissions
31%
16%
21%
3%
22%
21%
35%
35%
Waste management
Notes: a SGM sector mitigation estimates for Transportation Demand and Industry Production are not complete global representation due to varying levels of regional aggregation. b MERGE sector mitigation estimates for Industry Production, Agriculture, and Waste Management are aggregated. No Forestry mitigation options were modelled. c WIAGEM sector mitigation estimates do not sum to global total due to the breakout of the household and chemical sectors. d MiniCAM CO mitigation from Industrial Production is accounted for in the Industry Demand. 2 e Higher IPAC Agriculture emissions in the stabilization scenario than in the reference case reflects the loss of permanent forest due to growing bioenergy crops. f GRAPE Waste sector mitigation reflects only GDP activity factor changes in 2030, and reflects emission factor reductions in later years. g IPAC Waste sector cost-effective mitigation options are included in the baseline. h GRAPE CO from cement production is included in Buildings Demand. 2
with lower Category I and II stabilization targets, higher levels of short-term mitigation are required to achieve the target in the long run, resulting in a higher range of prices. Emission reductions of approximately 35% can be achieved at a price of 9–92 US$/tCO2-eq. Several of the models included in the EMF-21 study also ran multi-gas scenarios that included forest sinks as a mitigation option. Table 3.14 shows the 2030 mitigation estimates for these scenarios that model net land-use change (including forest carbon sinks) as a mitigation option. When terrestrial sinks are modelled as a mitigation option, it can lessen the pressure to mitigate in other sectors. Further discussion of forest
sequestration as a mitigation option is presented in Section 3.3.5.5. Across the higher Category IV stabilization target scenarios, emission reductions of 4–24% from the reference case emissions across all greenhouse gases can be achieved at a price of 2–21 US$/tCO2-eq. In scenarios with lower Category I and II stabilization targets, emission reductions of 26–40% can be achieved at a price of 31–121 US$/tCO2-eq. 3.6.2.2
Assessment of reduction levels at different marginal prices
To put these identified mitigation opportunities into context they will be compared with mitigation estimates from bottom-up 237
Issues related to mitigation in the long-term context
Chapter 3
Table 3.14: Global emission reductions from top-down models in 2030 (by sector) for multi-gas plus sinks scenarios.
Model Stabilization categories Stabilization target
Sector mitigaiton estimates in 2030 (total all gases GtCO2-eq)
Carbon price in 2030 (2000 US$/tCO2-eq) Reference emissions 2030 Total all gases (GtCO2-eq) Energy supply: electric Energy supply: non-electric Transportation demand Buildings demand Industry demand
Industry production Agriculture Forestry Waste management Global total Mitigation as % reference emissions
GRAPE
IMAGE 2.2
IMAGE 2.3
MESSAGE
MESSAGE
4.5 Wm2 from preIndustrial
4.5 Wm2 from preIndustrial
Category VI 4.5 Wm2 from preIndustrial
2
18
57.0
IMAGE 2.3 Category III 3.7 Wm2 from preIndustrial
21
B2 scenario, 4.5 Wm2 from preIndustrial 6
A2 scenario, 4.5 Wm2 from preIndustrial 15
65.5
59.7
57.8
70.9
59.7
59.7
57.8
0.5
2.4
1.7
1.1
7.3
3.9
8.7
4.3
0.0
2.2
1.6
0.5
3.5
2.3
3.7
2.2
0.0
1.3
0.7
0.3
1.0
1.5
2.8
2.2
0.3 Included in Buildings demand 0.1b 0.3 0.9 0.0a 2.1 4%
0.8 0.8
0.3 0.5
0.5 0.1
1.2 0.4
0.5 1.6
1.0 3.2
1.4 0.8
1.1 0.7 1.4 0.7 11.5 18%
0.8 0.6 0.3 1.0 7.6 13%
0.3 0.6 0.0 0.9 4.4 8%
0.6 1.5 0.2 1.1 16.8 24%
1.1 1.0 0.2 1.0 13.0 40%
2.0 1.2 0.2 1.1 24.0 40%
0.8 1.7 0.6 0.9 15.0 26%
50
IMAGE 2.3
MESSAGE
Category I/II 3.0 Wm2 B2 from prescenario, Industrial 3.0 Wm2 from preIndustrial 121 31
Notes: a GRAPE Waste sector mitigation reflects only GDP activity factor changes in 2030, and reflects emission factor reductions in later years. b GRAPE CO from cement production is included in Buildings Demand. 2
238
30
Gt CO2-eq/yr
25
20
10
5
0 10 0
101
100 US$/tCO2
15
50 US$/tCO2
Economy-wide reduction levels Figure 3.40 shows the available data from studies that report economy-wide reduction levels (multi-gas) and permit prices. The data has been taken from the emission scenario database (Hanaoka et al., 2006; Nakicenovic et al., 2006) – and information directly reported in the context of EMF-21 (De la Chesnaye and Weyant, 2006) and IMCP (Edenhofer et al., 2006). The total sets suggest some form of a relationship with
studies reporting higher permit prices: also, in general, reporting higher reduction levels.
20 US$/tCO2
models. Chapters 4 through 10 describe mitigation technologies available in specific economic sectors. Chapter 11, Section 11.3 compares the short-term mitigation estimates across all of the economic sectors for selected marginal costs levels (20, 50 and 100 US$/tCO2-eq). For that purpose, we have plotted the permit price and (sectoral) reduction levels of the different studies. These plots have been used to explore whether the combination of the studies suggests certain likely reduction levels at the three target levels of 20, 50 and 100 US$/tCO2-eq. As far more studies were available that reported economy-wide reduction levels than the ones that provided sectoral information, we were able to use a formal statistical method for the former. For the latter, a statistical method was also applied, but outcomes have been used with more care.
102
10 3
Carbon price (US$/tCO2-eq.) Figure 3.40: Permit price versus level of emission reduction – total economy in 2030 (the natural logarithm of the permit price is used for the x-axis). The uncertainty range indicated is the 68% interval.
Chapter 3
Issues related to mitigation in the long-term context
Energy supply 16
Buildings
Transport
Gt CO2-eq
4
Gt CO2-eq
4
Gt CO2-eq
14 12
3
3
2
2
1
1
10 8 6 4 2 0
0
0 1
10
100
1
Industry (consumption) 4
Gt CO2-eq
10
1
100
10
Industry (total)
Industry (process) 4
100
Gt CO2-eq
6
Gt CO2-eq
5 3
3 4
2
2
1
1
3 2 1
0
0
0 1
10
100
1
10
Gt CO2-eq
4
Gt CO2-eq
4
3
3
3
2
2
2
1
1
1
1
10
Carbon price (US$/tCO2-eq)
100
100
Gt CO2-eq
0
0
0
10
Waste management
Forestry
Agriculture 4
1
100
1
10
100
Carbon price (US$/tCO2-eq)
1
10
100
Carbon price (US$/tCO2-eq)
Figure 3.41: Permit price versus emission reduction level – several sectors in 2030 (vertical lines indicate levels at 20, 50 and 100 US$/tCO2).
Obviously, a considerable range of results is also found – this is a function of factors such as: • Model uncertainties, including technology assumptions and inertia. • Assumed baseline developments. • The trajectory of the permit price prior to 2030. The suggested relationship across the total is linear if permit prices are plotted on a logarithmic scale as shown in Figure 3.40. In other words, the relationship between the two variables is logarithmic, which is a form that is consistent with the general form of marginal abatement curves reported in literature: increasing reduction levels for higher prices, but diminishing returns at higher prices as the reduction tends to reach a theoretical maximum. The figure not only shows the best-guess regression
line, but also 68% confidence interval. The latter can be used to derive the 68 percentile interval of the reduction potential for the 20 and 100 US$/tCO2-eq price levels, which are 13.3 ± 4.6 GtCO2-eq/yr and 21.5 ± 4.7 GtCO2-eq/yr, respectively. Sectoral estimates A more limited set of studies reported sectoral reduction levels. The same plot as Figure 3.40 has been made for the sectoral data (see Figure 3.41), again plotting the logarithm of the permit price against emission reduction levels. The data here are directly taken from Table 3.13 and Table 3.14. As less data are available, the statistical analysis becomes less robust. Nevertheless, for most sectors, a similarly formed relationship was found across the set of studies as for the economy-wide potential (logarithmic relationship showing increasing reduction 239
Issues related to mitigation in the long-term context
Chapter 3
Table 3.15: Reduction potential at various marginal prices, averages across different models (low and high indicate one standard deviation variation).
20 US$/tCO2-eq
50 US$/tCO2-eq
100 US$/tCO2-eq
Low
High
Low
High
Low
High
Energy supply
3.9
9.7
6.7
12.4
8.7
14.5
Transport
0.1
1.6
0.5
1.9
0.8
2.5
Buildings
0.2
1.1
0.4
1.3
0.6
1.5
Industry
1.2
3.2
2.2
4.3
3.0
5.0
Agriculture
0.6
1.2
0.8
1.4
0.9
1.5
Forestry
0.2
0.8
0.2
0.8
0.2
0.8
Waste
0.7
0.9
0.8
1.0
0.9
1.1
Overall1
8.7
17.9
13.7
22.6
16.8
26.2
Note: 1) The overall potential has been estimated separately from the sectoral totals.
levels at relatively low prices, and a much slower increase at higher prices). As expected, in several sectors, the spread across models in the 2030 set is larger than in the economy-wide estimates. In general, a relatively strong relationship is found in the sectors for energy supply, transport, and industrial energy consumption. The relationship between the price and emission reduction level is less clear in other sectors – and more-or-less absent for the limited reported data on the forestry sector. It should be noted here that definitions across studies may be less well-defined – and also, forest sector emissions may actually increase in mitigation scenarios as a result of net deforestation due to bio-energy production. It should be noted that emission data (and thus also reduction levels) are reported on a ‘point of emission basis’ (emissions are reported for the sectors in which the emissions occur). For example, the efficiency improvements in end-use sectors for electricity lead to reductions in the energy supply sector. Likewise, using bio-energy leads to emission reductions in the end-use sectors, but at the same time (in some models) may lead to increases in emissions for forestry, due to associated landuse changes. The latter may explain differences in the way that data from top-down models are represented elsewhere in this report, as here (in most cases) only the emission changes from mitigation measures in the forestry sector itself are reported. It also explains why the potential in some of the end-use sectors is relatively small, as emission reductions from electricity savings are reported elsewhere. Reported estimates On the basis of the available data, the following ranges have been estimated for the reduction potential at a 20, 50 and 100 US$/tCO2-eq price (Table 3.15). As estimates have been made independently, the total of the different sectors does not add up to the overall range (as expected, the sum of the sectors gives a slightly wider range).
240
The largest potential is found in energy supply – covering both the electricity sector and energy supply – with a relatively high capability of responding to permit prices. Relatively high reduction levels are also found for the industry sector. Relatively small reduction levels are reported for the forestry sector and the waste management sector.
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4 Energy Supply Coordinating Lead Authors: Ralph E.H. Sims (New Zealand), Robert N. Schock (USA)
Lead Authors: Anthony Adegbululgbe (Nigeria), Jørgen Fenhann (Denmark), Inga Konstantinaviciute (Lithuania), William Moomaw (USA), Hassan B. Nimir (Sudan), Bernhard Schlamadinger (Austria), Julio Torres-Martínez (Cuba), Clive Turner (South Africa), Yohji Uchiyama (Japan), Seppo J.V. Vuori (Finland), Njeri Wamukonya (Kenya), Xiliang Zhang (China)
Contributing Authors: Arne Asmussen (Germany), Stephen Gehl (USA), Michael Golay (USA), Eric Martinot (USA)
Review Editors: Hans Larsen (Denmark), José Roberto Moreira (Brazil)
This chapter should be cited as: R.E.H. Sims, R.N. Schock, A. Adegbululgbe, J. Fenhann, I. Konstantinaviciute, W. Moomaw, H.B. Nimir, B. Schlamadinger, J. Torres-Martínez, C. Turner, Y. Uchiyama, S.J.V. Vuori, N. Wamukonya, X. Zhang, 2007: Energy supply. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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Table of Contents Executive Summary .................................................. 253 4.1
Introduction ...................................................... 256 4.1.1
4.2
4.3
252
4.4
4.4.1. Carbon dioxide emissions from energy supply by 2030 ........................................................... 289
Summary of Third Assessment Report (TAR) .... 258
Status of the sector .......................................... 258 4.2.1
Global development trends in the energy sector (production and consumption) ......................... 261
4.2.2
Emission trends of all GHGs ............................ 261
4.2.3
Regional development trends .......................... 262
4.2.4
Implications of sustainable development and energy access ................................................. 263
Mitigation costs and potentials of energy supply ................................................................. 289
4.5
4.4.2
Cost analyses.................................................. 290
4.4.3
Evaluation of costs and potentials for low-carbon, energy-supply technologies ............................. 293
4.4.4
Electricity-supply sector mitigation potential and cost of GHG emission avoidance ..................... 299
Policies and instruments ................................ 305 4.5.1
Emission reduction policies ............................. 305
Primary energy resource potentials, supply chain and conversion technologies .............. 264
4.5.2
Air quality and pollution .................................. 309
4.5.3
Co-benefits of mitigation policies ..................... 310
4.3.1
Fossil fuels ...................................................... 265
4.5.4
4.3.2
Nuclear energy ................................................ 268
Implications of energy supply on sustainable development ................................................... 311
4.3.3
Renewable energy ........................................... 272
4.5.5
Vulnerability and adaptation ............................. 313
4.3.4
Energy carriers ................................................ 280
4.5.6
Technology Research, Development, Demonstration, plus Deployment (RD3) ............ 313
4.3.5
Combined heat and power (CHP)..................... 284
4.3.6
Carbon dioxide capture and storage (CCS) ...... 284
4.3.7
Transmission, distribution, and storage ............ 286
4.3.8
Decentralized energy ....................................... 288
4.3.9
Recovered energy ........................................... 289
References ................................................................... 315
Chapter 4
Energy Supply
EXECUTIVE SUMMARY Annual total greenhouse gas (GHG) emissions arising from the global energy supply sector continue to increase. Combustion of fossil fuels continues to dominate a global energy market that is striving to meet the ever-increasing demand for heat, electricity and transport fuels. GHG emissions from fossil fuels have increased each year since the IPCC 2001 Third Assessment Report (TAR) (IPCC,2001), despite greater deployment of low- and zero-carbon technologies, (particularly those utilizing renewable energy); the implementation of various policy support mechanisms by many states and countries; the advent of carbon trading in some regions, and a substantial increase in world energy commodity prices. Without the near-term introduction of supportive and effective policy actions by governments, energyrelated GHG emissions, mainly from fossil fuel combustion, are projected to rise by over 50% from 26.1 GtCO2eq (7.1 GtC) in 2004 to 37–40 GtCO2 (10.1–10.9 GtC) by 2030. Mitigation has therefore become even more challenging. Global dependence on fossil fuels has led to the release of over 1100 GtCO2 into the atmosphere since the mid-19th century. Currently, energy-related GHG emissions, mainly from fossil fuel combustion for heat supply, electricity generation and transport, account for around 70% of total emissions including carbon dioxide, methane and some traces of nitrous oxide (Chapter 1). To continue to extract and combust the world’s rich endowment of oil, coal, peat, and natural gas at current or increasing rates, and so release more of the stored carbon into the atmosphere, is no longer environmentally sustainable, unless carbon dioxide capture and storage (CCS) technologies currently being developed can be widely deployed (high agreement, much evidence). There are regional and societal variations in the demand for energy services. The highest per-capita demand is by those living in Organisation for Economic Co-operation and Development (OECD) economies, but currently, the most rapid growth is in many developing countries. Energy access, equity and sustainable development are compromised by higher and rapidly fluctuating prices for oil and gas. These factors may increase incentives to deploy carbon-free and low-carbon energy technologies, but conversely, could also encourage the market uptake of coal and cheaper unconventional hydrocarbons and technologies with consequent increases in carbon dioxide (CO2) emissions. Energy access for all will require making available basic and affordable energy services using a range of energy resources and innovative conversion technologies while minimizing GHG emissions, adverse effects on human health, and other local and regional environmental impacts. To accomplish this would require governments, the global energy industry and society as a whole to collaborate on an unprecedented scale. The method used to achieve optimum integration of heating, cooling, electricity and transport fuel provision with more
efficient energy systems will vary with the region, local growth rate of energy demand, existing infrastructure and by identifying all the co-benefits (high agreement, much evidence). The wide range of energy sources and carriers that provide energy services need to offer long-term security of supply, be affordable and have minimal impact on the environment. However, these three government goals often compete. There are sufficient reserves of most types of energy resources to last at least several decades at current rates of use when using technologies with high energy-conversion efficient designs. How best to use these resources in an environmentally acceptable manner while providing for the needs of growing populations and developing economies is a great challenge. • Conventional oil reserves will eventually peak as will natural gas reserves, but it is uncertain exactly when and what will be the nature of the transition to alternative liquid fuels such as coal-to-liquids, gas-to-liquids, oil shales, tar sands, heavy oils, and biofuels. It is still uncertain how and to what extent these alternatives will reach the market and what the resultant changes in global GHG emissions will be as a result. • Conventional natural gas reserves are more abundant in energy terms than conventional oil, but they are also distributed less evenly across regions. Unconventional gas resources are also abundant, but future economic development of these resources is uncertain. • Coal is unevenly distributed, but remains abundant. It can be converted to liquids, gases, heat and power, although more intense utilization will demand viable CCS technologies if GHG emissions from its use are to be limited. • There is a trend towards using energy carriers with increased efficiency and convenience, particularly away from solid fuels to liquid and gaseous fuels and electricity. • Nuclear energy, already at about 7% of total primary energy, could make an increasing contribution to carbonfree electricity and heat in the future. The major barriers are: long-term fuel resource constraints without recycling; economics; safety; waste management; security; proliferation, and adverse public opinion. • Renewable energy sources (with the exception of large hydro) are widely dispersed compared with fossil fuels, which are concentrated at individual locations and require distribution. Hence, renewable energy must either be used in a distributed manner or concentrated to meet the higher energy demands of cities and industries. • Non-hydro renewable energy-supply technologies, particularly solar, wind, geothermal and biomass, are currently small overall contributors to global heat and electricity supply, but are the most rapidly increasing. Costs, as well as social and environmental barriers, are restricting this growth. Therefore, increased rates of deployment may need supportive government policies and measures. • Traditional biomass for domestic heating and cooking still accounts for more than 10% of global energy supplies but could eventually be replaced, mainly by modern biomass and 253
Energy Supply
other renewable energy systems as well as by fossil-based domestic fuels such as kerosene and liquefied petroleum gas (LPG) (high agreement, much evidence – except traditional biomass). Security of energy supply issues and perceived future benefits from strategic investments may not necessarily encourage the greater uptake of lower carbon-emitting technologies. The various concerns about the future security of conventional oil, gas and electricity supplies could aid the transition to more low-carbon technologies such as nuclear, renewables and CCS. However, these same concerns could also encourage the greater uptake of unconventional oil and gaseous fuels as well as increase demand for coal and lignite in countries with abundant national supplies and seeking national energy-supply security. Addressing environmental impacts usually depends on the introduction of regulations and tax incentives rather than relying on market mechanisms. Large-scale energy-conversion plants with a life of 30–100 years give a slow rate of turnover of around 1–3% per year. Thus, decisions taken today that support the deployment of carbon-emitting technologies, especially in countries seeking supply security to provide sustainable development paths, could have profound effects on GHG emissions for the next several decades. Smaller-scale, distributed energy plants using local energy resources and lowor zero-carbon emitting technologies, can give added reliability, be built more quickly and be efficient by utilizing both heat and power outputs locally (including for cooling). Distributed electricity systems can help reduce transmission losses and offset the high investment costs of upgrading distribution networks that are close to full capacity. More energy-efficient technologies can also improve supply security by reducing future energy-supply demands and any associated GHG emissions. However, the present adoption path for these, together with low- and zero-carbon supply technologies, as shown by business-as-usual baseline scenarios, will not reduce emissions significantly. The transition from surplus fossil fuel resources to constrained gas and oil carriers, and subsequently to new energy supply and conversion technologies, has begun. However it faces regulatory and acceptance barriers to rapid implementation and market competition alone may not lead to reduced GHG emissions. The energy systems of many nations are evolving from their historic dependence on fossil fuels in response to the climate change threat, market failure of the supply chain, and increasing reliance on global energy markets, thereby necessitating the wiser use of energy in all sectors. A rapid transition toward new energy supply systems with reduced carbon intensity needs to be managed to minimize economic, social and technological risks and to co-opt those stakeholders who retain strong interests in maintaining the status quo. The electricity, building and industry sectors are beginning 254
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to become more proactive and help governments make the transition happen. Sustainable energy systems emerging as a result of government, business and private interactions should not be selected on cost and GHG mitigation potential alone but also on their other co-benefits. Innovative supply-side technologies, on becoming fully commercial, may enhance access to clean energy, improve energy security and promote environmental protection at local, regional and global levels. They include thermal power plant designs based on gasification; combined cycle and supercritical boilers using natural gas as a bridging fuel; the further development and uptake of CCS; second-generation renewable energy systems; and advanced nuclear technologies. More efficient energy supply technologies such as these are best combined with improved end-use efficiency technologies to give a closer matching of energy supply with demand in order to reduce both losses and GHG emissions. Energy services are fundamental to achieving sustainable development. In many developing countries, provision of adequate, affordable and reliable energy services has been insufficient to reduce poverty and improve standards of living. To provide such energy services for everyone in an environmentally sound way will require major investments in the energy-supply chain, conversion technologies and infrastructure (particularly in rural areas) (high agreement, much evidence). There is no single economic technical solution to reduce GHG emissions from the energy sector. There is however good mitigation potential available based on several zero-or lowcarbon commercial options ready for increased deployment at costs below 20 US$/tCO2 avoided or under research development. The future choice of supply technologies will depend on the timing of successful developments for advanced nuclear, advanced coal and gas, and second-generation renewable energy technologies. Other technologies, such as CCS, secondgeneration biofuels, concentrated solar power, ocean energy and biomass gasification, may make additional contributions in due course. The necessary transition will involve more sustained public and private investment in research, development, demonstration and deployment (RD3) to better understand our energy resources, to further develop cost-effective and -efficient low- or zero-carbon emitting technologies, and to encourage their rapid deployment and diffusion. Research investment in energy has varied greatly from country to country, but in most cases has declined significantly in recent years since the levels achieved soon after the oil shocks during the 1970s. Using the wide range of available low- and zero-carbon technologies (including large hydro, bioenergy, other renewables, nuclear and CCS together with improved powerplant efficiency and fuel switching from coal to gas), the total mitigation potential by 2030 for the electricity sector alone, at carbon prices below 20 US$/tCO2-eq, ranges between 2.0 and 4.2 GtCO2-eq/yr. At the high end of this range, the
Chapter 4
over 70% share of fossil fuel-based power generation in the baseline drops to 55% of the total. Developing countries could provide around half of this potential. This range corresponds well with the TAR analysis potential of 1.3–2.5 GtCO2-eq/yr at 27 US$/tCO2-eq avoided, given that the TAR was only up to 2020 and that, since it was published in 2001, there has been an increase in development and deployment of renewable energy technologies, a better understanding of CCS techniques and a greater acceptance of improved designs of nuclear power plants. For investment costs up to 50 US$/tCO2-eq, the total mitigation potential by 2030 rises to between 3.0 and 6.4 GtCO2-eq/yr avoided. Up to 100 US$/tCO2-eq avoided, the total potential is between 4.0 and 7.2 GtCO2-eq/yr, mainly coming from non-OECD/EIT countries (medium agreement, limited evidence). There is high agreement in the projections that global energy supply will continue to grow and in the types of energy likely to be used by 2030. However, there is only medium confidence in the regional energy demand assumptions and the future mix of conversion technologies to be used. Overall, the future costs and technical potentials identified should provide a reasonable basis for considering strategies and decisions over the next several decades. No single policy instrument will ensure the desired transition to a future secure and decarbonized world. Policies will need to be regionally specific and both energy and nonenergy co-benefits should be taken into account. Internalizing environmental costs requires development of policy initiatives, long-term vision and leadership based on sound science and economic analysis. Effective policies supporting energysupply technology development and deployment are crucial to the uptake of low-carbon emission systems and should be regionally specific. A range of policies is already in place to encourage the development and deployment of low-carbonemitting technologies in OECD countries as well as in nonOECD countries including Brazil, Mexico, China and India. Policies in several countries have resulted in the successful
Energy Supply
implementation of renewable energy systems to give proven benefits linked with energy access, distributed energy, health, equity and sustainable development. Nuclear energy policies are also receiving renewed attention. However, the consumption of fossil fuels, at times heavily subsidized by governments, will remain dominant in all regions to meet ever-increasing energy demands unless future policies take into account the full costs of environmental, climate change and health issues resulting from their use. Energy sector reform is critical to sustainable energy development and includes reviewing and reforming subsidies, establishing credible regulatory frameworks, developing policy environments through regulatory interventions, and creating market-based approaches such as emissions trading. Energy security has recently become an important policy driver. Privatization of the electricity sector has secured energy supply and provided cheaper energy services in some countries in the short term, but has led to contrary effects elsewhere due to increasing competition, which, in turn, leads to deferred investments in plant and infrastructure due to longer-term uncertainties. In developed countries, reliance on only a few suppliers, and threats of natural disasters, terrorist attacks and future uncertainty about imported energy supplies add to the concerns. For developing countries lack of security and higher world-energy prices constrain endeavours to accelerate access to modern energy services that would help to decrease poverty, improve health, increase productivity, enhance competition and thus improve their economies (high agreement, much evidence). In short, the world is not on course to achieve a sustainable energy future. The global energy supply will continue to be dominated by fossil fuels for several decades. To reduce the resultant GHG emissions will require a transition to zeroand low-carbon technologies. This can happen over time as business opportunities and co-benefits are identified. However, more rapid deployment of zero- and low-carbon technologies will require policy intervention with respect to the complex and interrelated issues of: security of energy supply; removal of structural advantages for fossil fuels; minimizing related environmental impacts, and achieving the goals for sustainable development.
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4.1
Introduction
This chapter addresses the energy-supply sector and analyses the cost and potential of greenhouse gas (GHG) mitigation from the uptake of low- and zero-carbon-emitting technologies (including carbon capture and storage) over the course of the next two to three decades. Business-as-usual fossil-fuel use to meet future growth in energy demand will produce significant increases in GHG emissions. To make a transition by 2030 will be challenging. Detailed descriptions of the various technologies have been kept to a minimum, especially for those that have changed little since the Third Assessment Report (TAR) as they are well covered elsewhere (e.g., IEA, 2006a). The main goal of all energy transformations is to provide energy services that improve quality of life (e.g. health, life expectancy and comfort) and productivity (Hall et al., 2004). A supply of secure, equitable, affordable and sustainable energy is vital to future prosperity. Approximately 45% of final consumer energy is used for low-temperature heat (cooking, water and space heating, drying), 10% for high-temperature industrial process heat, 15% for electric motors, lighting and electronics and 30% for transport. The CO2 emissions from meeting this energy demand using mainly fossil fuels account for around 80% of total global emissions (IEA, 2006b). Demands for all forms of energy continue to rise to meet expanding economies and increases in world population. Rising prices and concerns about insecure energy supplies will compromise growth in fossil fuel consumption.
Primary energy sources
Energy supply is intimately tied in with development in the broad sense. At present, the one billion people living in developed (OECD) countries consume around half of the 470 EJ current annual global primary energy use (IEA, 2006b), whereas the one billion poorest people in developing countries consume only around 4%, mainly in the form of traditional biomass used inefficiently for cooking and heating. The United Nations has set Millennium Development Goals to eradicate poverty, raise living standards and encourage sustainable economic and social development (UN, 2000). Economic policies aimed at sustainable development can bring a variety of co-benefits including utilizing new energy technologies and improved access to adequate and affordable modern energy services. This will determine how many humans can expect to achieve a decent standard of living in the future (Section 4.5.4; Chapter 3). There are risks to being unprepared for future energy-supply constraints and disruptions. Currently, fossil fuels provide almost 80% of world energy supply; a transition away from their traditional use to zero- and low-carbon-emitting modern energy systems (including carbon dioxide capture and storage (CCS) (IPCC, 2005), as well as improved energy efficiency, would be part solutions to GHG-emission reduction. It is yet to be determined which technologies will facilitate this transition and which policies will provide appropriate impetus, although security of energy supply, aligned with GHG-reduction goals, are co-policy drivers for many governments wishing to ensure that future generations will be able to provide for their own well-being without their need for energy services being compromised.
Coal Oil Gas Uranium Hydro Biomass Wind Solar Geothermal Ocean energy
Prospecting Exploration Extraction Refining Distribution
Energy carriers
Heat
Solid fuels
Liquid fuels
Gaseous fuels
Storage
Heat Wholesale and retail energy markets Demand for energy services
Transport sector
Building sector
Direct electricity
Distribution
Transport fuels
$ / litre
Recovered energy from air and water
Electricity
$ / kWh
Combined heat and power
$ / GJ
Industry sector
$ / tonne
Primary industry
Traditional cooking Organic wastes water, space heating and wastewater
Figure 4.1: Complex interactions between primary energy sources and energy carriers to meet societal needs for energy services as used by the transport (Chapter 5), buildings (6), industry (7) and primary industry (8 and 9) sectors.
256
Chapter 4
Energy Supply
A mix of options to lower the energy per unit of GDP and carbon intensity of energy systems (as well as lowering the energy intensity of end uses) will be needed to achieve a truly sustainable energy future in a decarbonized world. Energyrelated GHG emissions are a by-product of the conversion and delivery sector (which includes extraction/refining, electricity generation and direct transport of energy carriers in pipelines, wires, ships, etc.), as well as the energy end-use sectors (transport, buildings, industry, agriculture, forestry and waste), as outlined in Chapters 5 to 10 (Figure 4.1). In all regions of the world energy demand has grown in recent years (Figure 4.2). A 65% global increase above the 2004 primary energy demand (464 EJ, 11,204 Mtoe) is anticipated by 2030 under business as usual (IEA, 2006b). Major investment will be needed, mostly in developing countries. As a result, without effective mitigation, total energy-related carbon dioxide emissions (including transformations, own use and losses) will rise from 26.1 GtCO2 (7.2 GtC) in 2004 to around 37–40 GtCO2 (11.1 GtC) in 2030 (IEA, 2006b; Price and de la Rue du Can, 2006), possibly even higher (Fisher, 2006), assuming modest energy-efficiency improvements are made to technologies currently in use. This means that all cost-effective means of reducing carbon emissions would need to be deployed in order to slow down the rate of increase of atmospheric concentrations (WBCSD, 2004; Stern, 2006). Implementing any major energy transition will take time. The penetration rates of emerging energy technologies depend on the expected lifetime of capital stock, equipment and the relative cost. Some large-scale energy-conversion plants can have an operational life of up to 100 years giving a slow rate of turnover, but around 2–3% per year replacement rate is more usual (Section 4.4.3). There is, therefore, some resistance to 4000
Mtoe
3500 3000 2500 2000 1500 1000 500 0
North Latin Europe EECCA Middle America America East
Africa
Asia
Figure 4.2: Global annual primary energy demand (including traditional biomass), 1971 – 2003 by region. Note: EECCA = countries of Eastern Europe, the Caucasus and Central Asia. 1000 Mtoe = 42 EJ. Source: IEA, 2004a.
change, and breakthroughs in technology to increase penetration rate are rare. Technology only diffuses rapidly once it can compete economically with existing alternatives or offers added value (e.g. greater convenience), often made possible by the introduction of new regulatory frameworks. It took decades to provide the largescale electricity and natural-gas infrastructures now common in many countries. Power stations, gas and electricity distribution networks and buildings are usually replaced only at the end of their useful life, so early action to stabilize atmospheric GHGs to have minimal impact on future GDP, it is important to avoid building ‘more of the same’ (Stern, 2006). Total annual capital investment by the global energy industry is currently around 300 billion US$. Even allowing for improved energy efficiency, if global energy demand continues to grow along the anticipated trajectory, by 2030 the investment over this period in energy-carrier and -conversion systems will be over 20 trillion (1012) US$, being around 10% of world total investment or 1% of cumulative global GDP (IEA, 2006b). This will require investment in energy-supply systems of around 830 billion US$/yr, mainly to provide an additional 3.5 TW of electricity-generation plant and transmission networks, particularly in developing countries, and provide opportunities for a shift towards more sustainable energy systems. Future investment in state-of-the-art technologies in countries without embedded infrastructure may be possible by ‘leapfrogging’ rather than following a similar historic course of development to that of OECD nations. New financing facilities are being considered because of the G8 Gleneagles Communiqué on Climate Change, Clean Energy and Sustainable Development of July 2005 (World Bank, 2006). It is uncertain how future investments will best meet future energy demand while achieving atmospheric GHG stabilization goals. There are many possible scenarios somewhere between the following extremes (WEC, 2004a). • High demand growth, giving very large productivity increases and wealth. Being technology- and resourceintensive, investment in technological changes would yield rapid stock turnover with consequent improvements in energy intensity and efficiency. • Reduced energy demand, with an investment goal to reduce CO2 emissions by one per cent per year by 2100. This would be technologically challenging and assumes unprecedented progressive international cooperation focused explicitly on developing a low-carbon economy that is both equitable and sustainable, requiring improvements in end-use efficiency and aggressive changes in lifestyle to emphasize resource conservation and dematerialization. The last century has seen a decline in the use of solids relative to liquids and gases. In the future, the use of gases is expected to increase (Section 4.3.1). The share of liquids will probably remain constant but with a gradual transition from conventional 257
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Chapter 4
4.2
oil (Section 4.3.1.3) toward coal-to-liquids, unconventional oils (Section 4.3.1.4) and modern biomass (Section 4.3.3.3). A robust mix of energy sources (fossil, renewable and nuclear), combined with improved end-use efficiency, will almost certainly be required to meet the growing demand for energy services, particularly in many developing countries. Technological development, decentralized non-grid networks, diversity of energy-supply systems and affordable energy services are imperative to meeting future demand. In many OECD countries, historical records show a decrease in energy per capita. Energy reduction per unit of GDP is also becoming apparent with respect to energy supplies in developing countries such as China (Larson et al., 2003). 4.1.1
Summary of Third Assessment Report (TAR)
Energy-supply and end-use-efficiency technology options (Table 3.36, TAR) showed special promise for reducing CO2 emissions from the industrial and energy sectors. Opportunities included more efficient electrical power generation from fossil fuels, greater use of renewable technologies and nuclear power, utilization of transport biofuels, biological carbon sequestration and CCS. It was estimated that potential reductions of 350– 700 MtC/yr (1.28–2.57 GtCO2-eq/yr) were possible in the energy supply and conversion sector by 2020 for <100 US$/C (27.3 US$/tCO2) (Table 3.37, TAR) divided equally between developed and developing countries. Improved end-use efficiency held greater potential for reductions. There are still obstacles to implementing the low-carbon technologies and measures identified in the TAR. These include a lack of human and institutional capacity; regulatory impediments and imperfect capital markets that discourage investment, including for decentralized systems; uncertain rates of return on investment; high trade tariffs on emission-lowering technologies; lack of market information, and intellectual property rights issues. Adoption of renewable energy is constrained by high investment costs, lack of capital, government support for fossil fuels and lack of government support mechanisms. The problem of ‘lock-in’ by existing technologies and the economic, political, regulatory, and social systems that support them were seen as major barriers to the introduction of low-emission technologies in all types of economies. This has not changed. Several technological innovations such as ground-source heat pumps, solar photovoltaic (PV) roofing, and offshore wind turbines have been recently introduced into the market as a result of multiple drivers including economic profit or productivity gains, non-energy-related benefits, tax incentives, environmental benefits, performance efficiency and other regulations. Lower GHG emissions were not always a major driver in their adoption. Policy changes in development assistance (Renewables, 2004) and direct foreign investment provide opportunities to introduce low-emission technologies to developing countries more rapidly. 258
Status of the sector
Providing energy services from a range of sources to meet society’s demands should offer security of supply, be affordable and have minimal impact on the environment. However, these three goals often conflict. Recent liberalization of energy markets in many countries has led to cheaper energy services in the short term, but in the longer term, investments with longer write-off periods and often lower returns (including nuclear power plants and oil refineries) are not always being made due to the need to maximize value for short-term shareholders. Energy-supply security has improved in some countries but deteriorated elsewhere due to increasing competition, which, because of insecurity, leads to deferred investments in grid and plants. Addressing environmental impacts, including climate
a) Thermal-power energy and losses in the production of one unit of useful light energy. Gas or coal
Generation
Transmission Distribution Wiring
320
112
106
65%
5%
101
100
Custumer Lamp 2
Useful Fitting light 1
1
primary energy
% loss
5%
1%
98%
50%
b) Investment in more efficient gas-fired power stations reduces fuel inputs by around 30%. Gas or coal
Generation
Transmission Distribution Wiring
224
112
106
50%
5%
101
100
Custumer Lamp 2
Useful Fitting light 1
1
primary energy
% loss
5%
1%
98%
50%
c) Investment in energy-saving compact fluorescent lightbulbs reduces fuel inputs by around 80%. Gas or coal
Generation
Transmission Distribution Wiring
64
22
21
200
100
Custumer Lamp 2
Useful Fitting light 1
1
primary energy
% loss
65%
5%
5%
1%
90%
50%
Figure 4.3: The conversion from primary energy to carriers and end-uses is an essential driver of efficiency, exemplified here by the case of lighting. Primary fuel inputs can be reduced using more efficient generation plants, but also to a greater degree by more energy-efficient technologies (as described in Chapters 5, 6 and 7) Source: Cleland, 2005.
Chapter 4
change, usually depends on laws and tax incentives rather than market mechanisms (Section 13.2.1.1). Primary energy sources are: fossil carbon fuels; geothermal heat; fissionable, fertile and fusionable nuclides; gravitational (tides) and rotational forces (ocean currents), and the solar flux. These must be extracted, collected, concentrated, transformed, transported, distributed and stored (if necessary) using technologies that consume some energy at every step of the supply chain (Figure 4.3). The solar flux provides both
Energy Supply
intermittent energy forms including wind, waves and sunlight, and stored energy in biomass, ocean thermal gradients and hydrologic supplies. Energy carriers such as heat, electricity and solid, liquid and gaseous fuels deliver useful energy services. The conversion of primary energy-to-energy carriers and eventually to energy services creates losses, which, together with distribution losses, represent inefficiencies and cost of delivery (Figure 4.4).
Figure 4.4: Global energy flows (EJ in 2004) from primary energy through carriers to end-uses and losses. Related carbon dioxide emissions from coal, gas and oil combustion are also shown, as well as resources (vertical bars to the left). Notes: See also Table 4.2. Note that the IEA (2006b) data on known reserves and estimated resources, as used here, differ from the data in Table 4.2 that uses a breakdown in conventional and unconventional. The latter category may include some quantities shown as resources in Figure 4.26. 1) The current capacity of energy carriers is shown by the width of the lines. 2) Further energy conversion steps may take place in the end-use sectors, such as the conversion of natural gas into heat and/or electricity on site at the individual consumer level. 3) ‘Buildings’ include residential, commercial, public service and agricultural. 4) Peat is included with coal. Organic waste is included with biomass. 5) The resource efficiency ratio by which fast-neutron technology increases the power-generation capability per tonne of natural uranium varies greatly from the OECD assessment of 30:1 (OECD, 2006b). In this diagram the ratio used is up to 240:1 (OECD,2006c). 6) Comparisons can be made with SRES B2 scenario projections for 2030 energy supply, as shown in Figure 4.26. Source: IEA, 2006b.
259
Energy Supply
Chapter 4
Analysis of energy supply should be integrated with energy carriers and end use since all these aspects are inextricably and reciprocally dependent. Energy-efficiency improvements in the conversion of primary energy resources into energy carriers during mining, refining, generation etc. continue to occur but are relatively modest. Reducing energy demand by the consumer using more efficient industrial practices, buildings, vehicles and appliances also reduces energy losses (and hence CO2 emissions) along the supply chain and is usually cheaper and more efficient than increasing the supply capacity (Chapters 5, 6 and 7 and Figure 4.3). Since 1971, oil and coal remain the most important primary energy sources with coal increasing its share significantly since 2000 (Figure 4.5). Growth slowed in 2005 and the total share of fossil fuels dropped from 86% in 1971 to 81% in 2004, (IEA, 2006b) excluding wind, solar, geothermal, bioenergy and biofuels, as well as non-traded traditional biomass. Combustible biomass and wastes contributed approximately 10% of primary energy consumption (IEA, 2006b) with more than 80% used for traditional fuels for cooking and heating in developing countries. Around 40% of global primary energy was used as fuel to generate 17,408 TWh of electricity in 2004 (Figure 4.4). Electricity generation has had an average growth rate of 2.8%/yr since 1995 and is expected to continue growing at a rate of 2.5–3.1%/yr until 2030 (IEA, 2006b; Enerdata, 2004). In 2005, hard coal and lignite fuels were used to generate 40% of world electricity production with natural gas providing 20%, nuclear 16%, hydro 16%, oil 7% and other renewables 2.1% (IEA 2006b). Non-hydro renewable energy power plants have
14000
Mtoe Other renewables Hydro Nuclear Biomass
12000 10000
Gas
8000 6000
Coal
4000 2000 0 1971
Oil 1980
1990
2000
2005
Figure 4.5: World primary energy consumption by fuel type. Note: The IEA convention is to assume a 33% conversion efficiency when calculating the primary energy equivalent of nuclear energy from gross generation. The conversion efficiencies of a fossil fuel or nuclear power plant are typically about 33% due to heat losses whereas the energy in stored water (and other non-thermal means) is converted in turbines at efficiencies approaching 100%. Thus, for a much lower energy equivalent, hydro can produce the same amount of electricity as a thermal plant without a system to utilize the waste heat. 1000 Mtoe = 42 EJ. Source: IEA, 2006b.
260
expanded substantially in the past decade with wind turbine and solar PV installations growing by over 30% annually. However, they still supply only a small portion of electricity generation (Enerdata, 2004). Many consumers of petroleum and, to a lesser degree, natural gas depend to varying but significant amounts of fuels imported from distant, often politically unstable regions of the world and transported through a number of locations equally vulnerable to disruptions. For example, in 2004 16.5–17 Mbbl/d of oil was shipped through the Straits of Hormuz in the Persian Gulf and 11.7 Mbbl/d through the Straits of Malacca in Asia (EIA/DOE, 2005). A disruption in supply at either of these points could have a severe impact on global oil markets. Political unrest in some oil and gas producing regions of Middle East, Africa and Latin America has also highlighted the vulnerability of supply. When international trade in oil and gas expands in the near future, the risks of supply disruption may increase leading to more serious impacts (IEA, 2004b; CIEP, 2004). This is a current driver for shifting to less vulnerable renewable energy resources. Whereas fossil fuel sources of around 100,000 W/m2 land area have been discovered at individual locations, extracted and then distributed, renewable energy is usually widely dispersed at densities of 1–5 W/m2 and hence must either be used in a distributed manner or concentrated to meet the high energy demands of cities and industries. For renewable energy systems, variations in climate may produce future uncertainties result from dry years for hydro, poor crop yields for biomass, increased cloud cover and materials costs for solar, and variability in annual wind speeds. However, over their lifetime they are relatively price-stable sources and in a mixed portfolio of technologies can avoid losses from fluctuating oil, gas and power prices (Awerbuch and Sauter, 2005) unless their owner also has to sell based on volatile short-term prices (Roques et al., 2006). World oil and gas prices in 2005 and 2006 were significantly higher than most pre-2005 scenario models predicted. This might lead to a reduction in transportation use and GHG emissions (Chapter 5), but conversely could also encourage a shift to coal-fired power plants. Hence, high energy prices do not necessarily mean increased investments in low carbon technologies or lower GHG emissions. For nuclear power, investment uncertainties exist due to financial markets commanding a higher interest rate to cover perceived risks, thus increasing the cost of capital and thereby generation costs. Increasing environmental concerns will also raise the costs of obtaining permits. Conversely, surplus uranium supplies may possibly lower fuel prices, but this represents a relatively low fraction of generation costs compared with fossilfuel power stations (Hagen et al., 2005).
Chapter 4
4.2.1
Energy Supply
Global development trends in the energy sector (production and consumption)
From 1900 to 2000, world primary energy increased more than ten-fold, while world population rose only four-fold from 1.6 billion to 6.1 billion. Most energy forecasts predict considerable growth in demand in the coming decades due to increasing economic growth rates throughout the world but especially in developing countries. Global primary-energy consumption rose from 238 EJ in 1972 to 464 EJ in 2004 (Chapter 1). During the period 1972 to 1990, the average annual growth was 2.4%/yr, dropping to 1.4%/yr from 1990 to 2004 due to the dramatic decrease in energy consumption in the former Soviet Union (FSU) (Figure 4.2) and to energy intensity improvements in OECD countries. The highest growth rate in the last 14 years was in Asia (3.2%/yr).
8 7 6
There is a large discrepancy between primary energy consumption per capita of 336 GJ/yr for the average North American to around 26 GJ/yr for the average African (Enerdata, 2004). The region with the lowest per-capita consumption has changed from Asian developing countries in 1972 to African countries today. 4.2.2
Emission trends of all GHGs
Growing global dependence on coal, oil and natural gas since the mid-19th century has led to the release of over 1100 GtCO2 into the atmosphere (IPCC, 2001). Global CO2 emissions from fuel combustion (around 70% of total GHG emissions and 80% of total CO2) temporarily stabilized after the two oil crises in 1973 and 1979 before growth continued (Figure 4.6). (Emission data can be found at UNFCCC, 2006 and EEA, 2005). Analyses of potential CO2 reductions for energy-supply options (for example IPCC, 2001; Sims et al., 2003a; IEA/NEA, 2005; IEA, 2006b) showed that emissions from the energy-supply sector have grown at over 1.5% per year from around 20 GtCO2 (5.5 GtC) in 1990 to over 26 GtCO2 (7 GtC) by 2005. The European Union’s CO2 emissions almost stabilized in this period mainly due to reductions by Germany, Sweden, and UK, but offset by increases by other EU-15 members (BP, 2004) such that total CO2 emissions had risen 6.5% by 2004. Other OECD country emissions increased by 20% during the same period, Brazil by 68%, and Asia by 104%. From 1990 to 2005, China’s CO2 emissions increased from 676 to 1,491 MtCO2/yr to become 18.7% of global emissions (IEEJ, 2005; BP, 2006) second only to the US. Carbon emissions from non OECD Europe and the FSU dropped by 38% between 1989
OECD North America Asia
5 OECD Europe
4
Non-OECD Europe and EECCA
3 2 OECD Pacific 1
Middle East
Latin America
Africa
0
19
Low electrification rates correlate with slow socio-economic development. The average rates in the Middle East, North Africa, East Asia/China and Latin America have resulted in grid connection for over 85% of their populations, whereas subSaharan Africa is only 23% (but only 8% in rural regions) and South Asia is 41% (30% in rural regions) (IEA, 2005c).
Gt CO2
71
75
19
80
19
85
19
90
19
95
19
00
20
04
20
Figure 4.6: Global trends in carbon dioxide emissions from fuel combustion by region from 1971 to 2004. Note: EECCA = countries of Eastern Europe, the Caucasus and Central Asia. Source: IEA, 2006b.
and 1999 but have since started to increase as their economies rebound. Natural gas and nuclear gained an increased market share after the oil crises in the 1970s and continue to play a role in lowering GHG emissions, along with renewable energy. Continuous technical progress towards non-carbon energy technologies and energy-efficiency improvements leads to an annual decline in carbon intensity. The carbon intensity of global primary energy use declined from 78 gCO2/MJ in 1973 to 61 gCO2/MJ in 2000 (BP, 2005) mainly due to diversification of energy supply away from oil. China’s carbon-intensity reduction was around 5%/yr during the period 1980 to 2000 with 3%/yr expected out to 2050 (Chen, 2005), although recent revision of China’s GDP growth for 2004 by government officials may affect this prediction. The US has decreased its GHG intensity (GHG/unit GDP) by 2% in 2003 and 2.5% in 2004 (Snow, 2006) although actual emissions rose. For the power generation and heat supply sector, emissions were 12.7.GtCO2-eq in 2004 (26% of total) including 2.2 GtCO2eq from methane (31% of total) and traces of N2O (Chapter 1). In 2030, according to the World Energy Outlook 2006 baseline (IEA, 2006b), these will have increased to 17.7 GtCO2-eq. During combustion of fossil fuels and biomass, nitrous oxide, as well as methane, is produced. Methane emissions from natural gas production, transmission and distribution are uncertain (UNFCCC, 2004). The losses to the atmosphere reported to the UNFCCC in 2002 were in the range 0.3–1.6% of the natural gas consumed. For more than a decade, emissions from flaring and venting of the gas associated with oil extraction have remained stable at about 0.3 GtCO2-eq/yr. Developing 261
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Chapter 4
countries accounted for more than 85% of this emission source (GGFR, 2004). Coal bed methane (CBM, Section 4.3.1.2) is naturally contained in coal seams and adjacent rock strata. Unless it is intentionally drained and captured from the coal and rock the process of coal extraction will continue to liberate methane into the atmosphere. Around 10% of total anthropogenic methane emissions in the USA are from this source (US EPA, 2003). The 13 major coal-producing countries together produce 85% of worldwide CBM estimated to be 0.24 GtCO2-eq in 2000. China was the largest emitter (0.1 GtCO2-eq) followed by the USA (0.04 GtCO2-eq), and Ukraine (0.03 GtCO2-eq). Total CBM emissions are expected to exceed 0.3 GtCO2-eq in 2020 (US EPA, 2003) unless mitigation projects are implemented. Other GHGs are produced by the energy sector but in relatively low volumes. SF6 is widely used in high-voltage gasinsulated substations, switches and circuit breakers because of its high di-electric constant and electrical insulating properties (Section 7.4.8). Its 100-year global warming potential (GWP) is 23,900 times that of CO2 and it has a natural lifetime in the atmosphere of 3200 years, making it among the most potent of heat-trapping gases. Approximately 80% of SF6 sales go to power utilities and electric power equipment manufacturers. The US government formed a partnership with 62 electric power generators and utilities (being about 35% of the USA
power grid) to voluntarily reduce leakage of SF6 from electrical equipment and the release rate dropped from 17% of stocks to 9% between 1999 and 2002. This represented a 10% reduction from the 1999 baseline to 0.014 GtCO2-eq (EPA, 2003). Australia and the Netherlands also have programmes to reduce SF6 emissions and a voluntary agreement in Norway should lead to 13% reductions by 2005 and 30% by 2010 below their 2000 release rates. CFC-114 is used as a coolant in gaseous diffusion enrichment for nuclear power, but its GHG contribution is small compared to CO2 emissions (Dones et al., 2005). 4.2.3
Regional development trends
World primary energy demand is projected to reach 650– 890EJ by 2030 based on A1 and B2 SRES scenarios and the Reference scenario of the IEA’s World Energy Outlook 2004 (Price and de la Rue du Can, 2006). All three scenarios show Asia could surpass North American energy demand by around 2010 and be close to doubling it by 2030. Africa, the Middle East and Latin America could double their energy demand by 2030; sub-Saharan Africa and the Former Soviet Union may both reach 60–70 EJ, and Pacific OECD and Central and Eastern Europe will be less than 40 EJ each. Demand is more evenly distributed among regions in the B2 scenario, with Central and Eastern Europe and the Pacific OECD region reducing future demand. A similar pattern is evident for final consumer energy (Table 4.1).
Table 4.1: Final energy consumption and carbon dioxide emissions for all sectors by region to 2030 based on assumptions from three baseline scenarios. Region
WEO 2004 Reference 2002
2010
2020
SRES A1 Marker 2030
2000
2010
2020
SRES B2 Marker 2030
2000
2010
2020
2030
Final energy (EJ) Pacific OECD
23.6
26.6
29.5
30.9
21.5
24.6
29.8
36.6
23.5
26.5
30.0
32.3
Canada/US
70.2
78.3
87.4
94.6
71.3
79.3
89.8
99.2
71.0
82.4
93.3
104.1
Europe
51.5
56.7
62.3
66.5
52.0
58.9
67.6
74.6
46.9
51.3
54.4
57.9
EIT
27.0
31.0
35.9
40.5
38.4
42.6
50.1
58.8
32.0
37.5
44.8
52.7
Latin America
18.6
23.0
29.7
37.6
23.5
42.1
63.2
81.7
20.9
27.8
33.1
39.6
Africa/Middle East
28.4
35.4
44.8
54.3
36.4
57.2
87.6
123.7
25.6
32.6
40.2
53.1
Asia
66.8
83.1
105.3
128.3
71.5
100.6
143.9
194.6
69.4
92.5
122.0
157.5
286.2
334.0
395.0
452.8
314.6
405.3
532.0
669.1
289.2
350.6
417.6
497.2
World
Emissions (GtCO2) Pacific OECD
2.12
2.32
2.52
2.53
2.42
2.62
2.89
3.12
2.10
2.33
2.28
2.10
Canada/US
6.47
7.24
7.88
8.32
5.84
6.08
6.13
5.97
6.61
7.63
8.36
8.43
Europe
4.12
4.45
4.81
4.90
4.21
4.53
4.74
4.73
3.95
4.04
4.07
4.13
EIT
2.39
2.79
3.21
3.54
2.97
3.45
3.71
3.85
3.23
3.26
3.66
4.08
Latin America
1.34
1.678
2.21
2.89
1.67
3.38
4.99
6.16
1.41
1.99
2.29
2.69
Africa/Middle East
2.01
2.51
3.40
4.21
2.50
4.89
7.55
10.29
1.98
2.39
2.85
3.90
Asia
5.52
7.33
9.91
12.66
5.82
9.85
14.32
18.53
5.58
7.47
9.65
12.12
Int. marine bunkers
0.46
0.47
0.48
0.51
23.98
28.33
33.93
39.03
25.42
34.81
44.33
52.65
24.86
29.10
33.15
37.46
World
Source: Price and De la Rue du Can, 2006
262
Chapter 4
Energy Supply
The World Energy Council projected 2000 data out to 2050 for three selected scenarios with varying population estimates (WEC, 2004d). The IEA (2003c) and IPCC SRES scenarios (Chapter 3) did likewise. Implications of sustainable development were that primary energy demands are likely to experience a 40 to 150% increase, with emissions rising to between 48 and 55 GtCO2/yr. This presents difficulties for the energy-supply side to meet energy demand. It requires technical progress and capital provision, and provides challenges for minimizing the environmental consequences and sustainability of the dynamic system. Electricity is expected to grow even more rapidly than primary energy by between 110 and 260% up to 2050, presenting even more challenges in needing to build power production and transmission facilities, mostly in developing countries.
and a sharp downturn in GHG emissions resulted. Although increasing more recently, emissions remain some 30% below 1990 levels (IEA, 2003a; Figure 4.2). Despite the economic and political transformations, energy systems in EIT countries are still characterized by overcapacity in electricity production, high dependency on fossil-fuel imports and inefficient use (IEA, 2003b). Market reforms have been accompanied with the opening of these economies, leading to their integration into the European and global economies. Growth is likely to accelerate faster in those countries that have achieved EU membership (IEA, 2003b). The total primary-energy consumption of EIT has increased by 2% per year since 2000 and is expected to increase steadily over the next couple of decades as income levels and economic outputs expand, unless energy efficiency manages to stabilize demand.
The Asia-Pacific region has almost 30% of proven coal resources but otherwise is highly dependent on imported energy, particularly oil, which is now the largest source of primary commercial energy consumed in the region. In 2003, 82% of imported oil came from the Middle East and the region will continue to depend on OPEC countries. A continuation of China’s rapid annual economic growth of 9.67% from 1990 to 2003 (CSY, 2005) will result in continued new energy demand, primary energy consumption having increased steadily since the 1980s. Energy consumption in 2003 reached 49 EJ. High air pollution in China is directly related to energy consumption, particularly from coal combustion that produces 70% of national particulate emissions, 90% of SO2, 67% of N2O and 70% of CO2 (BP, 2004).
Latin America, Africa and the Middle East are expected to double their energy demand over the next two to three decades and to retain their shares of global energy demand (IEA, 2005a; Price and de la Rue du Can, 2006). Policies in developing countries aimed at energy-supply security, reducing environmental impacts and encouraging a free market economy (Section 4.5.1.1) may help encourage market efficiency, energy conservation, common oil-reserve storage, investment in resource exploration, implementation of the Clean Development Mechanism (CDM) and international carbon emission trading. International cooperation will continue to play a role in the development of energy resources and improvement of industrial productivity. 4.2.4
Increased use of natural gas has recently occurred throughout the Asian region, although its share of 12% of primary energy remains lower than the 23% and 17% shares in the United States and the European Union, respectively (BP, 2006). A liquefied natural gas (LNG) market has recently emerged in the region, dominated by Japan, South Korea and Spain, who together provide about 68% of worldwide trade flows. Primary energy consumption in the Asia-Pacific region due to continued overall economic growth and increasing transport fuel demand is estimated to increase by 1.0% annually over the period 2002–2030 in OECD Asia, 2.6% in China, 2.1% in India, and 2.7% in Indonesia (IEA, 2004a). This will then account for 42% of the increase in world primary-energy demand. The region could be faced with overall energy resource shortages in the coming decades (Komiyama et al., 2005). Energy security risks are likely to increase and stricter environmental restrictions on fossil fuel consumption could be imposed. Nuclear power (Section 4.3.2), hydropower (Section 4.3.3.1) and other renewables (Section 4.3.3) may play a greater role in electricity generation to meet the ever-rising demand. For economies in transition (EIT, mainly from the former Soviet Union), the total primary energy consumption in 2000 (Figure 4.6) was only 70% of the 1990 level (Enerdata, 2004)
Implications of sustainable development and energy access
Analysis from 125 countries indicated that well-being and level of development correlate with the degree of modern energy services consumed per capita in each country (Bailis et al., 2005) (Figure 4.7). Lack of energy access frustrates the aspirations of many developing countries (OECD, 2004a). Without improvement, the United Nations’ Millennium Development Goals (MDGs)
toe per capita 0-1.5 1.5-3 3-4.5 4,5-6 <6
Figure 4.7: Global annual energy consumption per capita by region (toe/capita). Source: BP, 2004.
263
Energy Supply
Chapter 4
of halving the proportion of people living on less than a dollar a day by 2015 (UN, 2000) will be difficult to meet. Achieving this target implies a need for increased access to electricity and expansion of modern cooking and heating fuels for millions of people in developing countries mainly in South Asia and sub-Saharan Africa (IEA, 2005a). Historical electricity access rates of 40 million people per annum in the 1980s and 30 million per annum in the 1990s suggest that current efforts to achieve the MDGs will need to be greatly exceeded. By 2030, around 2400 GW of new power plant capacity will be needed in developing countries (100 GW/yr), which, together with the necessary infrastructure, will require around 5 trillion US$ investment (IEA, 2006b). Ecological implications of energy supply result from coal and uranium mining, oil extraction, oil and gas transport, deforestation, erosion and river-flow disturbance. Certain synergetic effects can be achieved between renewable energy generation and ecological values such as reforestation and landscape structural improvements, but these are relatively minor.
4.3 Primary energy resource potentials, supply chain and conversion technologies This section discusses primary-supply and secondary-energy (carrier) technologies. Technologies that have developed little since the TAR are covered in detail elsewhere (e.g., IEA, 2006a). Energy flows proceed from primary sources through carriers to provide services for end-users (Figure 4.3). The status of energy sources and carriers is reviewed here along with their available resource potential and usage, conversion technologies, costs and environmental impacts. An analysis is made of the potential contributions due to further technological development for each resource to meet the world’s growing energy needs, but also to reduce atmospheric GHG emissions. Assessments of global energy reserves, resources and fluxes, together with cost ranges and sustainability issues, are summarized in Table 4.2.
Table 4.2: Generalized data for global energy resources (including potential reserves), annual rate of use (490 EJ in 2005), share of primary energy supply and comments on associated environmental impacts. Estimated available energy resourceb (EJ)
Rate of use in 2005 (EJ/yr)c
Coal (conventional) Coal (unconventional) Peatd Gas (conventional) Gas (unconventional) Coalbed methane Tight sands Hydrates Oil (conventional) Oil (unconventional)
>100,000 32,000 large 13,500 18,000 >8,000? 8,000 >60,000 10,000 35,000
120 0 0.2 100 Small 1.5 3.3 0 160 3
Nuclear
Uraniume Uranium recyclef Fusion
7,400 220,000 5 x 109 estimated
Renewableg
Hydro (>10 MW) Hydro (< 10 MW) Wind Biomass (modern) Biomass (traditional) Geothermal Solar PV Concentrating solar Ocean (all sources)
Energy class
Specific energy sourcea
Fossil energy
60 /yr 2 /yr 600 /yr 250 /yr 5,000 /yr 1,600 /yr 50 /yrh 7/yr (exploitable)
2005 share of total supply (%) 25 <0.1 21
Comments on environmental impacts Average 92.0 gCO2/MJ
Average 52.4 gCO2/MJ Unknown, likely higher
0.3 0.7 33 0.6
26 Very small 0
5.3
25 0.8 0.95 9 37 2 0.2 0.03 <1
5.1 0.2 0.2 1.8 7.6 0.4 <0.1 0.1 0
Average 76.3 gCO2/MJ Unknown, likely higher Spent fuel disposition Waste disposal Tritium handling Land-use impacts
Likely land-use for crops Air pollution Waterway contamination Toxics in manufacturing Small Land and coastal issues.
Notes: a See Glossary for definitions of conventional and unconventional. b Various sources contain ranges, some wider than others (e.g., those for conventional oil cluster much more closely than those for biomass). For the purposes of this assessment of mitigation potentials these values, generalized to a first approximation with some very uncertain, are more than adequate. c Hydro and wind are treated as equivalent energy to fossil and biomass since the conversion losses are much less (www.iea.org/textbase/stats/questionaire/faq.asp) d Peat land area under active production is approximately 230,000 ha. This is about 0.05% of the global peat land area of 400 million hectares (WEC, 2004c). e Once-through thermal reactors. f Light-water and fast-spectrum reactors with plutonium recycle g Data from 2005 is at www.ren21.net/globalstatusreport/issuesGroup.asp h Very uncertain. The potential of the Mediterranean area alone has been estimated by one source to be 8000 EJ/yr (http:/www.dlr.de/tt/med-csp) Sources: Data from BP, 2006; WEC, 2004c; IEA, 2006b; IAEA, 2005c; USGS, 2000; Martinot, 2005; Johansson, 2004; Hall, 2003; Encyclopaedia of Energy, 2004.
264
Chapter 4
4.3.1
Energy Supply
Fossil fuels
Fossil energy resources remain abundant but contain significant amounts of carbon that are normally released during combustion. The proven and probable reserves of oil and gas are enough to last for decades and in the case of coal, centuries (Table. 4.2). Possible undiscovered resources extend these projections even further. Fossil fuels supplied 80% of world primary energy demand in 2004 (IEA, 2006b) and their use is expected to grow in absolute terms over the next 20–30 years in the absence of policies to promote low-carbon emission sources. Excluding traditional biomass, the largest constituent was oil (35%), then coal (25%) and gas (21%) (BP, 2005). In 2003 alone, world oil consumption increased by 3.4%, gas by 3.3% and coal by 6.3% (WEC, 2004a). Oil accounted for 95% of the land-, water- and air-transport sector demand (IEA, 2005d) and, since there is no evidence of saturation in the market for transportation services (WEC, 2004a), this percentage is projected to rise (IEA, 2003c). IEA (2005b) projected that oil demand will grow between 2002 and 2030 (by 44% in absolute terms), gas demand will almost double, and CO2 emissions will increase by 62% (which lies between the SRES A1 and B2 scenario estimates of +101% and +55%, respectively; Table 4.1). Fossil energy use is responsible for about 85% of the anthropogenic CO2 emissions produced annually (IEA, 2003d). Natural gas is the fossil fuel that produces the lowest amount of GHG per unit of energy consumed and is therefore favoured in mitigation strategies. Fossil fuels have enjoyed economic advantages that other technologies may not be able to overcome, although there has been a recent trend for fossil fuel prices to increase and renewable energy prices to decrease because of continued productivity improvements and economies of scale. All fossil fuel options will continue to be used if matters are left solely to the market place to determine choice of energy conversion technologies. If GHGs are to be reduced significantly, either current uses of fossil energy will have to shift toward low- and zero-carbon sources, and/or technologies will have to be adopted that capture and store the CO2 emissions. The development and implementation of lowcarbon technologies and deployment on a larger scale requires considerable investment, which, however, should be compared with overall high investments in future energy infrastructure (see Section 4.1). 4.3.1.1
Coal and peat
Coal is the world’s most abundant fossil fuel and continues to be a vital resource in many countries (IEA, 2003e). In 2005, coal accounted for around 25% of total world energy consumption primarily in the electricity and industrial sectors (BP, 2005; US EIA, 2005; Enerdata, 2004). Global proven recoverable reserves of coal are about 22,000 EJ (BP, 2004; WEC, 2004b) with another 11,000 EJ of probable reserves and
an estimated additional possible resource of 100,000 EJ for all types. Although coal deposits are widely distributed, over half of the world’s recoverable reserves are located in the US (27%), Russia (17%) and China (13%). India, Australia, South Africa, Ukraine, Kazakhstan and the former Yugoslavia account for an additional 33% (US DOE, 2005). Two thirds of the proven reserves are hard coal (anthracite and bituminous) and the remainder are sub-bituminous and lignite. Together these resources represent stores of over 12,800 GtCO2. Consumption was around 120 EJ/yr in 2005, which introduced approximately 9.2 GtCO2/yr into the atmosphere. Peat (partially decayed plant matter together with minerals) has been used as a fuel for thousands of years, particularly in Northern Europe. In Finland, it provides 7% of electricity and 19% of district heating. Technologies The demand for coal is expected to more than double by 2030 and the IEA has estimated that more than 4500 GW of new power plants (half in developing countries) will be required in this period (IEA, 2004a). The implementation of modern high-efficiency and clean utilization coal technologies is key to the development of economies if effects on society and environment are to be minimized (Section 4.5.4). Most installed coal-fired electricity-generating plants are of a conventional subcritical pulverized fuel design, with typical efficiencies of about 35% for the more modern units. Supercritical steam plants are in commercial use in many developed countries and are being installed in greater numbers in developing countries such as China (Philibert and Podkanski, 2005). Current supercritical technologies employ steam temperatures of up to 600ºC and pressures of 280 bar delivering fuel to electricitycycle efficiencies of about 42% (Moore, 2005). Conversion efficiencies of almost 50% are possible in the best supercritical plants, but are more costly (Equitech, 2005; IPCC, 2001; Danish Energy Authority, 2005). Improved efficiencies have reduced the amount of waste heat and CO2 that would otherwise have been emitted per unit of electricity generation. Technologies have changed little since the TAR. Supercritical plants are now built to an international standard, however, and a CSIRO (2005) project is under way to investigate the production of ultra-clean coal that reduces ash below 0.25%, sulphur to low levels and, with combined-cycle direct-fired turbines, can reduce GHG emissions by 24% per kWh, compared with conventional coal power stations. Gasifying coal prior to conversion to heat reduces the emissions of sulphur, nitrogen oxides, and mercury, resulting in a much cleaner fuel while reducing the cost of capturing CO2 emissions from the flue gas where that is conducted. Continued development of conventional combustion integrated gasification combined cycle (IGCC) systems is expected to further reduce emissions. 265
Energy Supply
Coal-to-liquids (CTL) is well understood and regaining interest, but will increase GHG emissions significantly without CCS (Section 4.3.6). Liquefaction can be performed by direct solvent extraction and hydrogenation of the resulting liquid at up to 67% efficiency (DTI, 1999) or indirectly by gasification then producing liquids by Fischer-Tropsch catalytic synthesis as in the three SASOL plants in South Africa. These produce 0.15 Mbbl/day of synthetic diesel fuel (80%) plus naphtha (20%) at 37–50% thermal efficiency. Lower-quality coals would reduce the thermal efficiency whereas co-production with electricity and heat (at a 1:8 ratio) could increase it and reduce the liquid fuel costs by around 10%. Production costs of CTL appear competitive when crude oil is around 35–45 US$/bbl, assuming a coal price of 1 US$/ GJ. Converting lignite at 0.50 US$/GJ close to the mine could compete with production costs of about 30 US$/bbl. The CTL process is less sensitive to feedstock prices than the gas-toliquids (GTL) process, but the capital costs are much higher (IEA, 2005e). An 80,000 barrel per day CTL installation would cost about 5 billion US$ and would need at least 2–4 Gt of coal reserves available to be viable. 4.3.1.2
Gaseous fuels
Chapter 4
currently under development, such as so-called ‘H’ designs, may have efficiencies approaching 60% using high combustion temperatures, steam-cooled turbine blades and more complex steam cycles. Despite rising prices, natural gas is forecast to continue to be the fastest-growing primary fossil fuel energy source worldwide (IEA, 2006b), maintaining average growth of 2.0% annually and rising to 161 EJ consumption in 2025. The industrial sector is projected to account for nearly 23% of global natural gas demand in 2030, with a similar amount used to supply new and replacement electric power generation. The share of natural gas used to generate electricity worldwide is projected to increase from 25% of primary energy in 2004 to 31% in 2030 (IEA, 2006b). LNG Meeting future increases in global natural gas demand for direct use by the industrial and commercial sectors as well as for power generation will require development and scaleup of liquefied natural gas (LNG) as an energy carrier. LNG transportation already accounts for 26% of total international natural gas trade in 2002, or about 6% of world natural gas consumption and is expected to increase substantially.
Conventional natural gas Natural gas production has been increasing in the Middle East and Asia–Oceania regions since the 1980s. Globally, from 1994–2004, it showed an annual growth rate of 2.3%. During 2005, 11% of natural gas was produced in the Middle East, while Europe and Eurasia produced 38%, and North America 27% (BP, 2006). Natural gas presently accounts for 21% of global consumption of modern energy at around 100 EJ/yr, contributing around 5.5 GtCO2 annually to the atmosphere.
The Pacific Basin is the largest LNG-producing region in the world, supplying around 50% of all global exports in 2002 (US EIA, 2005). The share of total US natural gas consumption met by net imports of LNG is expected to grow from about 1% in 2002 to 15% (4.5 EJ) in 2015 and to over 20% (6.8 EJ) in 2025. Losses during the LNG liquefaction process are estimated to be 7 to 13% of the energy content of the withdrawn natural gas being larger than the typical loss of pipeline transportation over 2000 km.
Proven global reserves of natural gas are estimated to be 6500 EJ (BP, 2006; WEC, 2004c; USGS, 2004b). Almost three quarters are located in the Middle East, and the transitional economies of the FSU and Eastern Europe. Russia, Iran and Qatar together account for about 56% of gas reserves, whereas the remaining reserves are more evenly distributed on a regional basis including North Africa (BP, 2006). Probable reserves and possible undiscovered resources that expect to be added over the next 25 years account for 2500 EJ and 4500 EJ respectively (USGS, 2004a), although other estimates are less optimistic.
LPG Liquefied petroleum gas (LPG) is a mixture of propane, butane, and other hydrocarbons produced as a by-product of natural gas processing and crude oil refining. Total global consumption of LPG amounted to over 10 EJ in 2004 (MCH/ WLPGA, 2005), equivalent to 10% of global natural gas consumption (Venn, 2005). Growth is likely to be modest with current share maintained.
Natural gas-fired power generation has grown rapidly since the 1980s because it is relatively superior to other fossil-fuel technologies in terms of investment costs, fuel efficiency, operating flexibility, rapid deployment and environmental benefits, especially when fuel costs were relatively low. Combined cycle, gas turbine (CCGT) plants produce less CO2 per unit energy output than coal or oil technologies because of the higher hydrogen-carbon ratio of methane and the relatively high thermal efficiency of the technology. A large number of CCGT plants currently being planned, built, or operating are in the 100–500 MWe size range. Advanced gas turbines 266
Unconventional natural gas Methane stored in a variety of geologically complex, unconventional reservoirs, such as tight gas sands, fractured shales, coal beds and hydrates, is more abundant than conventional gas (Table 4.2). Development and distribution of these unconventional gas resources remain limited worldwide, but there is growing interest in selected tight gas sands and coalbed methane (CBM). Probable CBM resources in the US alone are estimated to be almost 800 EJ but less than 110 EJ is believed to be economically recoverable (USGS, 2004b) unless gas prices rise significantly. Worldwide resources may be larger than 8000 EJ, but a scarcity of basic information on the gas content of coal resources makes this number highly speculative.
Chapter 4
Energy Supply
Large quantities of tight gas are known to exist in geologically complex formations with low permeability, particularly in the US, where most exploration and production has been undertaken. However, only a small percentage is economically viable with existing technology and current US annual production has stabilized between 2.7 and 3.8 EJ. Methane gas hydrates occur naturally in abundance worldwide and are stable as deep marine sediments on the ocean floor at depths greater than 300m and in polar permafrost regions at shallower depths. The amount of carbon bound in hydrates is not well understood, but is estimated to be twice as large as in all other known fossil fuels (USGS, 2004a). Hydrates may provide an enormous resource with estimates varying from 60,000 EJ (USGS, 2004a) to 800,000 EJ (Encyclopedia of Energy, 2004). Recovering the methane is difficult, however, and represents a significant environmental problem if unintentionally released to the atmosphere during extraction. Safe and economic extraction technologies are yet to be developed (USGS, 2004a). Hydrates also contain high levels of CO2 that may have to be captured to produce pipeline-quality gas (Encyclopedia of Energy, 2004). The GTL process is gaining renewed interest due to higher oil prices, particularly for developing uneconomic natural gas reserves such as those associated with oil extraction at isolated gas fields which lie far from markets. As for CTL, the natural gas is turned into synthesis gas, which is converted by the Fischer-Tropsch process to synthetic fuels. At present, at least nine commercial GTL projects are progressing through various development stages in gas-rich countries such as Qatar, Iran, Russia, Nigeria, Australia, Malaysia and Algeria with worldwide production estimated at 0.58 Mbbl/day (FACTS, 2005). GTL conversion technologies are around 55% efficient and can help bring some of the estimated 6000 EJ of stranded gas resources to market. Production costs vary depending on gas prices, but where stranded gas is available at 0.5 US$/GJ production costs are around 30 US$ a barrel (IEA 2006a). Higher CO2 emissions per unit consumed compared with conventional oil products. 4.3.1.3
Petroleum fuels
Various studies and models have been used to forecast future oil production (US EIA, 2004; Bentley, 2005). Geological models take into consideration the volume and quality of hydrocarbons but do not include economic effects on price, which in turn has a direct effect on supply and the overall rate of recovery. Mathematical models generally use the historical as well as the observed patterns of production to estimate a peak (or several peaks) reached when half the reserves are consumed. Assessments of the amount of oil consumed, the amount remaining for extraction, and whether the peak oil tipping point is close or not, have been very controversial (Hirsch et al., 2005). Estimates of the ultimate extractable resource (proven + probable + possible reserves) with which the world was endowed have varied from less than 5730 EJ to 34,000 EJ (1000 to 6000 Gbbl), though the more recent predictions have all ranged between 11,500–17,000 EJ (2000–3000 Gbbl) (Figure 4.8). Over time, the prediction trend showed increasing resource estimates in the 1940s and 1950s as more fields were discovered. However, the very optimistic estimates of the 1970s were later discredited and a relatively constant estimate has since been observed. Specific analyses include Bentley (2002b), who concluded that 4870 EJ had been consumed by 1998 and that 6300 EJ will have been extracted by 2008. The US Geological Survey (USGS, 2000) the World Petroleum Congress and the IFP agreed that approximately 4580 EJ (800 Gbbl) have been consumed in the past 150 years and 5730 EJ (1000 Gbbl) of proven reserves remain. Other detailed analyses (e.g. USGS, 2000) also estimated there are 4150 EJ of probable and possible resources still available for extraction. Thus, the total available potential proven reserves plus resources of around 10,000 EJ (BP, 2004; WEC, 2004b) should be sufficient for about 70 years’
7000
Billion barrels
6000
Conventional oil products extracted from crude oil-well bores and processed by primary, secondary or tertiary methods represent about 37% of total world energy consumption (Figure 4.4 and Table 4.2) with major resources concentrated in relatively few countries. Two thirds of proven crude oil reserves are located in the Middle East and North Africa (IEA, 2005a).
5000
Known or proven reserves are those extractable at today’s prices and technologies. Additional probable and possible resources are based on historical experience in geological basins. While new discoveries have lagged behind production for more than 20 years, reserve additions from all sources including discoveries, extensions, revisions and improvements in oil recovery continue to outpace production (IEA, 2005b).
1000
4000 3000 2000
0 1920
1940
1960
1980
2000
2020
Figure 4.8: Estimates of the global ultimate extractable conventional oil resource by year of publications. Source: Based on Bentley, 2002a; Andrews and Udal, 2003.
267
Energy Supply
supply at present rates of consumption. Since consumption rates will continue to rise, however, 30 to 40 years’ supply is a more reasonable estimate (Hallock et al., 2004). Burning this amount of petroleum resources would release approximately 700 GtCO2 (200 GtC) into the atmosphere, about two thirds the amount released to date from all fossil-fuel consumption. Opportunities for energy-efficiency improvements in oil refineries and associated chemical plants are covered in Chapter 7. 4.3.1.4
Unconventional oil
As conventional oil supplies become scarce and extraction costs increase, unconventional liquid fuels, in addition to CTL and GTL, will become more economically attractive, but offset by greater environmental costs (Williams et al., 2006). Oil that requires extra processing such as from shales, heavy oils and oil (tar) sands is classified as unconventional. Resource estimates are uncertain, but together contributed around 3% of world oil production in 2005 (2.8 EJ) and could reach 4.6 EJ by 2020 (USGS, 2000) and up to 6 EJ by 2030 (IEA, 2005a). The oil industry has the potential to diversify the product mix, thereby adding to fuel-supply security, but higher environmental impacts may result and investment in new infrastructure would be needed. Heavy oil reserves are greater than 6870 EJ (1200 Gbbl) of oil equivalent with around 1550 EJ technically recoverable. The Orinoco Delta, Venezuela has a total resource of 1500 EJ with current production of 1.2 EJ/yr (WEC, 2004c). Plans for 2009 are to apply deep-conversion, delayed coking technology to produce 0.6 Mbbl/day of high-value transport fuels. Oil shales (kerogen that has not completed the full geological conversion to oil due to insufficient heat and pressure) represent a potential resource of 20,000 EJ with a current production of just 0.024 EJ/yr, mostly in the US, Brazil, China and Estonia. Around 80% of the total resource lies in the western US with 500 Gbbl of medium-quality reserves from rocks yielding 95 L of oil per tonne but with 1000 Gbbl potential if utilizing lowerquality rock. Mining and upgrading of oil shale to syncrude fuel costs around 11 US$/bbl. As with oil sands (below), the availability of abundant water is an issue. Around 80% of the known global tar sand resource of 15,000 EJ is in Alberta, Canada, which has a current production of 1.6 EJ/yr, representing around 15% of national oil demand. Around 310 Gbbl is recoverable (CAPP, 2006). Production of around 2 Mbbl/day by 2010 could provide more than half of Canada’s projected total oil production with 4 Mbbl/day possible by 2020. Total resources represent at least 400 Gt of stored carbon and will probably be added to as more are discovered, assuming that natural gas and water (steam) to extract the hydrocarbons are available at a reasonable cost. Technologies for recovering tar sands include open cast (surface) mining where the deposits are shallow enough (which 268
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accounts for 10% of the resource but 80% of current extraction), or injection of steam into wells in situ to reduce the viscosity of the oil prior to extraction. Mining requires over 100m3 of natural gas per barrel of bitumen extracted and in situ around 25m3. In both cases cleaning and upgrading to a level suitable for refining consumes a further 25–50m3 per barrel of oil feedstock. The mining process uses about four litres of water to produce one litre of oil but produces a refinable product. The in situ process uses about two litres of water to one of oil, but the very heavy product needs cleaning and diluting (usually with naptha) at the refinery or sent to an upgrader to yield syncrude at an energy efficiency of around 75% (NEB, 2006). The energy efficiency of oil sand upgrading is around 75%. Mining, producing and upgrading oil sands presently costs about 15 US$/bbl (IEA, 2006a) but new greenfield projects would cost around 30–35 US$/bbl due to project-cost inflation in recent years (NEB, 2006). If CCS is integrated, then an additional 5 US$ per barrel at least should be added. Comparable costs for conventional oil are 4–6 US$/bbl for exploration and production and 1–2 US$/bbl for refining. Mining of oil sands leaves behind large quantities of pollutants and areas of disturbed land. The total CO2 emitted per unit of energy during production of liquid unconventional oils is greater than for a unit of conventional oil products due to higher energy inputs for extraction and processing. Net emissions amount to 15– 34 kgCO2 (4–9 kgC) per GJ of transport fuel compared with around 5-10 kgCO2 (1.3-2.7 kgC) per GJ for conventional oil (IEA, 2005d, Woyllinowicz et al., 2005). Oil sands currently produce around 3–4 times the pre-combustion emissions (CO2/ GJ liquid fuel) compared with conventional oil extraction and refining, whereas large-scale production of oil-shale processing would be about 5 times, GTL 3–4 times, and CTL around 7–8 times when using sub-bituminous coal. The Athabascan oil-sands project has refining energy expenditures of 1 GJ energy input per 6 GJ bitumen processed, producing emissions of 11 kgCO2 (3 kgC) per GJ from refining alone, but with a voluntary reduction goal of 50% by 2010 (Shell, 2006). 4.3.2
Nuclear energy
In 2005, 2626 TWh of electricity (16% of the world total) was generated by nuclear power, requiring about 65,500 t of natural uranium (WNA, 2006a). As of December 2006, 442 nuclear power plants were in operation with a total installed capacity of about 370 GWe (WNA, 2006a). Six plants were in long-term shutdown and since 2000, the construction of 21 new reactors has begun (IAEA, 2006). The US has the largest number of reactors and France the highest percentage hare of total electricity generation. Many more reactors are either planned or proposed, mostly in China, India, Japan, Korea, Russia, South Africa and the US (WNA, 2006a). Nuclear power capacity forecasts out to 2030 (IAEA, 2005c; WNA, 2005a; Maeda, 2005; Nuclear News, 2005) vary between 279 and
Chapter 4
740 GWe when proposed new plants and the decommissioning of old plants are both considered. In Japan 55 nuclear reactors currently provide nearly a third of total national electricity with one to be shut down in 2010. Immediate plans for construction of new reactors have been scaled down due to anticipated reduced power demand due to greater efficiency and population decline (METI, 2005). The Japanese target is now to expand the current installed 50 GWe to 61 GWe by adding 13 new reactors with nine operating by 2015 to provide around 40% of total electricity (JAEC, 2005). In China there are nine reactors in operation, two under construction and proposals for between 28 and 40 new ones by 2020 (WNA, 2006b; IAEA, 2006) giving a total capacity of 41–46 GWe (Dellero & Chessé, 2006). To meet future fuel demand, China has ratified a safeguards agreement (ANSTO, 2006) enabling the future purchase of thousands of tonnes of uranium from Australia, which has 40% of the world’s reserves. In India seven reactors are under construction, with plans for 16 more to give 20 GWe of nuclear capacity installed by 2020 (Mago, 2004). Improved safety and economics are objectives of new designs of reactors. The worldwide operational performance has improved and the 2003–2005 average unit capacity factor was 83.3% (IAEA, 2006). The average capacity factors in the US increased from less than 60% to 90.9% between 1980 and 2005, while average marginal electricity-production costs (operation, maintenance and fuel costs) declined from 33 US$/ MWh in 1988 to 17 US$/MWh in 2005 (NEI, 2006). The economic competitiveness of nuclear power depends on plant-specific features, number of plants previously built, annual hours of operation and local circumstances. Full life-cycle cost analyses have been used to compare nuclear-generation costs with coal, gas or renewable systems (Section 4.4.2; Figure 4.27) (IEA/NEA, 2005) including: • investment (around 45–70% of total generation costs for design, construction, refurbishing, decommissioning and expense schedule during the construction period); • operation and maintenance (around 15–40% for operating and support staff, training, security, and periodic maintenance); and • fuel cycle (around 10–20% for purchasing, converting and enriching uranium, fuel fabrication, spent fuel conditioning, reprocessing, transport and disposal of the spent fuel). Decommissioning costs are below 500 US$/kW (undiscounted) for water reactors (OECD, 2003) but around 2500 US$/kW for gas-cooled (e.g. Magnox) reactors due to radioactive waste volumes normalized by power output being about ten times higher. The decommissioning and clean-up of the entire UK Sellafield site, including facilities not related to commercial nuclear power production, has been estimated to cost £31.8 billion or approximately 60 billion US$ (NDA, 2006). Total life-cycle GHG emissions per unit of electricity produced from nuclear power are below 40 gCO2-eq/kWh
Energy Supply
(10 gC-eq/kWh), similar to those for renewable energy sources (Figure 4.18). (WEC, 2004a; Vattenfall, 2005). Nuclear power is therefore an effective GHG mitigation option, especially through license extensions of existing plants enabling investments in retro-fitting and upgrading. Nuclear power currently avoids approximately 2.2–2.6 GtCO2/yr if that power were instead produced from coal (WNA, 2003; Rogner, 2003) or 1.5 GtCO2/yr if using the world average CO2 emissions for electricity production in 2000 of 540 gCO2/kWh (WEC, 2001). However, Storm van Leeuwen and Smith (2005) give much higher figures for the GHG emissions from ore processing and construction and decommissioning of nuclear power plants. 4.3.2.1
Risks and environmental impacts
Regulations demand that public and occupational radiation doses from the operation of nuclear facilities be kept as low as reasonably achievable and below statutory limits. Mining, milling, power-plant operation and reprocessing of spent fuel dominate the collective radiation doses (OECD, 2000). Protective actions for mill-tailing piles and ponds have been demonstrated to be effective when applied to prevent or reduce long-term impacts from radon emanation. In the framework of the IAEA’s Nuclear Safety Convention (IAEA, 1994), the IAEA member countries have agreed to maintain high safety culture to continuously improve the safety of nuclear facilities. However, risks of radiation leakage resulting from accidents at a power plant or during the transport of spent fuel remain controversial. Operators of nuclear power plants are usually liable for any damage to third parties caused by an incident at their installation regardless of fault (UIC, 2005), as defined by both international conventions and national legislation. In 2004, the contracting parties to the OECD Paris and Brussels Conventions signed Amending Protocols setting the minimum liability limit at 700 million € with additional compensation up to 800 € through public funds. Many non-OECD countries have similar arrangements through the IAEA’s Vienna Convention. In the US, the national Price-Anderson Act provides compensation up to 300 million US$ covered by an insurance paid by each reactor and also by a reactor-operator pool from the 104 reactors, which provides 10.4 billion US$. 4.3.2.2
Nuclear-waste management, disposal and proliferation aspects
The main safety objective of nuclear waste management (IAEA, 1997; IAEA, 2005b) is that human health and the environment need to be protected now and in the future without imposing undue burdens on future generations. Repositories are in operation for the disposal of low- and medium-level radioactive wastes in several countries but none yet exist for high-level waste (HLW) such as spent light-water reactor (LWR) fuel. Deep geological repositories are the most extensively studied option but resolution of both technical and political/ societal issues is still needed. 269
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In 2001, the Finnish Parliament agreed to site a spent fuel repository near the Olkiluoto nuclear power plant. After detailed rock-characterization studies, construction is scheduled to start soon after 2010 with commissioning planned for around 2020. In Sweden, a repository-siting process is concentrating on the comparison of several site alternatives close to the Oskarshamn and Forsmark nuclear power plants. In the US, the Yucca Mountain area has been chosen, amidst much controversy, as the preferred site for a HLW repository and extensive sitecharacterization and design studies are underway, although not without significant opposition. It is not expected to begin accepting HLW before 2015. France is also progressing on deep geological disposal as the reference solution for long-lived radioactive HLW and sets 2015 as the target date for licensing a repository and 2025 for opening it (DGEMP, 2006). Spentfuel reprocessing and recycling of separate actinides would significantly reduce the volume and radionuclide inventory of HLW. The enrichment of uranium (U-235), reprocessing of spent fuel and plutonium separation are critical steps for nuclearweapons proliferation. The Treaty on Non-Proliferation of Nuclear Weapons (NPT) has been ratified by nearly 190 countries. Compliance with the terms of the NPT is verified and monitored by the IAEA. Improving proliferation resistance is a key objective in the development of next-generation nuclear reactors and associated advanced fuel-cycle technologies. For once-through uranium systems, stocks of plutonium are continuously built up in the spent fuel, but only become
Chapter 4
accessible if reprocessed. Recycling through fast-spectrum reactors on the other hand allows most of this material to be burned up in the reactor to generate more power, although there are vulnerabilities in the reprocessing step and hence still the need for careful safeguards. Advanced reprocessing and partitioning and transmutation technologies could minimize the volumes and toxicity of wastes for geological disposal, yet uncertainties about proliferation-risk and cost remain. 4.3.2.3
Development of future nuclear-power systems
Present designs of reactors are classed as Generations I through III (Figure 4.9). Generation III+ advanced reactors are now being planned and could first become operational during the period 2010 –2020 (GIF, 2002) and state-of-the-art thereafter to meet anticipated growth in demand. These evolutionary reactor designs claim to have improved economics, simpler safety systems with the impacts of severe accidents limited to the close vicinity of the reactor site. Examples include the European design of a pressurized water reactor (EPR) scheduled to be operating in Finland around 2010 and the Flamanville 3 reactor planned in France. Generation IV nuclear-energy technologies that may become operational after about 2030 employ advanced closed-fuel cycle systems with more efficient use of uranium and thorium resources. Advanced designs are being pursued mainly by the Generation-IV International Forum (GIF, a group of ten nations plus the EU and coordinated by the US Department of Energy)
Figure 4.9: Evolution of nuclear power systems from Generation I commercial reactors in the 1950s up to the future Generation IV systems which could be operational after about 2030. Notes: LWR = light-water reactor; PWR = pressurized water reactor; BWR = boiling-water reactor; ABWR = advanced boiling-water reactor; CANDU = Canada Deuterium Uranium. Source: GIF, 2002.
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as well as the International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO) coordinated by the IAEA. The Global Nuclear Energy Partnership (US DOE, 2006), proposed by the US, has similar objectives. These initiatives focus on the development of reactors and fuel cycles that provide economically competitive, safe and environmentally sound energy services based on technology designs that exclude severe accidents, involve proliferation-resistant fuel cycles decoupled from any fuel-resource constraints, and minimize HLW. Much additional technology development would be needed to meet these long-term goals so strategic public RD&D funding is required, since there is limited industrial/commercial interest at this early stage. GIF has developed a framework to plan and conduct international cooperative research on advanced (breeder or burner) nuclear-energy systems (GIF, 2002) including three designs of fast-neutron reactor, (sodium-cooled, gas-cooled and lead-cooled) as well as high-temperature reactors. Reactor concepts capable of producing high-temperature nuclear heat are intended to be employed also for hydrogen generation, either by electrolysis or directly by special thermo-chemical water-splitting processes or steam reforming. There is also an ongoing development project by the South African utility ESKOM for an innovative high-temperature, pebble-bed modular reactor. Specific features include its smaller unit size, modularity, improved safety by use of passive features, lower power production costs and the direct gas-cycle design utilizing the Brayton cycle (Koster et al., 2003; NER, 2004). The supercritical light-water reactor is also one of the GIF concepts intended to be operated under supercritical water pressure and temperature conditions. Conceivably, some of these concepts may come into practical use and offer better prospects for future use of nuclear power. Experience of the past three decades has shown that nuclear power can be beneficial if employed carefully, but can cause great problems if not. It has the potential for an expanded role as a cost-effective mitigation option, but the problems of potential reactor accidents, nuclear waste management and disposal and nuclear weapon proliferation will still be constraining factors. 4.3.2.4
Uranium exploration, extraction and refining
In the long term, the potential of nuclear power is dependent upon the uranium resources available. Reserve estimates of the uranium resource vary with assumptions for its use (Figure 4.10). Used in typical light-water reactors (LWR) the identified resources of 4.7 Mt uranium, at prices up to 130 US$/kg, correspond to about 2400 EJ of primary energy and should be sufficient for about 100 years’ supply (OECD, 2006b) at the 2004 level of consumption. The total conventional proven (identified) and probable (yet undiscovered) uranium resources are about 14.8 Mt (7400 EJ). There are also unconventional uranium resources such as those contained in phosphate minerals, which are recoverable for between 60 and 100 US$/kg (OECD, 2004a).
160 000
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Figure 4.10: Estimated years of uranium-resource availability for various nuclear technologies at 2004 nuclear-power utilization levels. Source: OECD, 2006b; OECD, 2006c.
If used in present reactor designs with a ‘once-through’ fuel cycle, only a small percentage of the energy content is utilized from the fissile isotope U-235 (0.7% in natural uranium). Uranium reserves would last only a few hundred years at current rate of consumption (Figure 4.10). With fast-spectrum reactors operated in a ‘closed’ fuel cycle by reprocessing the spent fuel and extracting the unused uranium and plutonium produced, the reserves of natural uranium may be extended to several thousand years at current consumption levels. In the recycle option, fast-spectrum reactors utilize depleted uranium and only plutonium is recycled so that the uranium-resource efficiency is increased by a factor of 30 (Figure 4.10; OECD, 2001). Thereby the estimated enhanced resource availability of total conventional uranium resources corresponds to about 220,000 EJ primary energy (Table 4.2). Even if the nuclear industry expands significantly, sufficient fuel is available for centuries. If advanced breeder reactors could be designed in the future to efficiently utilize recycled or depleted uranium and all actinides, then the resource utilization efficiency would be further improved by an additional factor of eight (OECD, 2006c). Nuclear fuels could also be based on thorium with proven and probable resources being about 4.5 Mt (OECD, 2004a). Thorium-based fast-spectrum reactors appear capable of at least doubling the effective resource base, but the technology remains to be developed to ascertain its commercial feasibility (IAEA, 2005a). There are not yet sufficient commercial incentives for thorium-based reactors except perhaps in India. The thorium fuel cycle is claimed to be more proliferation-resistant than other fuel cycles since it produces fissionable U-233 instead of fissionable plutonium, and, as a by-product, U-232 that has a daughter nuclide emitting high-energy photons. 4.3.2.5
Nuclear fusion
Energy from the fusion of heavy hydrogen fuel (deuterium, tritium) is actively being pursued as a long-term almost 271
Energy Supply
Renewable energy
Renewable energy accounted for over 15% of world primary energy supply in 2004, including traditional biomass (7–8%), large hydro-electricity (5.3%, being 16% of electricity generated1), and other ‘new’ renewables (2.5%) (Table 4.2). Under the business-as-usual case of continued growing energy demand, renewables are not expected to greatly increase their market share over the next few decades without continued and sustained policy intervention. For example, IEA (2006b) projected in the Reference scenario that renewables will have dropped to a 13.7 % share of global primary energy (20.8 % of electricity) in 2030, or under the Alternative Policy scenario will have risen to 16.2 % (25.3 % of electricity). Renewable-energy systems can contribute to the security of energy supply and protection of the environment. These and other benefits of renewable energy systems were defined in a declaration by 154 nations at the Renewables 2004 conference held in Bonn (Renewables, 2004). Renewable-energy technologies can be broadly classified into four categories: 1) technologically mature with established markets in at least several countries:– large and small hydro, woody biomass combustion, geothermal, landfill gas, crystalline silicon PV solar water heating, onshore wind, bioethanol from sugars and starch (mainly Brazil and US); 2) technologically mature but with relatively new and immature markets in a small number of countries:– municipal solid waste-to-energy, anaerobic digestion, biodiesel, co-firing of biomass, concentrating solar dishes and troughs, solar-assisted air conditioning, mini- and micro-hydro and offshore wind; 3) under technological development with demonstrations or small-scale commercial application, but approaching wider market introduction:– thin-film PV, concentrating PV, tidal range and currents, wave power, biomass gasification and pyrolysis, bioethanol from ligno-cellulose and solar thermal towers; and 4) still in technology research stages:– organic and inorganic nanotechnology solar cells, artificial photosynthesis,
1
The most mature renewable technologies (large hydro, biomass combustion, and geothermal) have, for the most part, been able to compete in today’s energy markets without policy support. Solar water heating, solar PV in remote areas, wind farms on exceptional sites, bioethanol from sugar cane, and forest residues for combined heat and power (CHP) are also competitive today in the best locations. In countries with the most mature markets, several forms of ‘new’ renewable energy can compete with conventional energy sources on an averagecost basis, especially where environmental externalities and fossil fuel price risks are taken into account. In countries where market deployment is slow due to less than optimal resources, higher costs (relative to conventional fuels) and/or a variety of market and social barriers, these technologies still require government support (IEA, 2006e). Typical construction costs for new renewable energy power plants are high, between 1000 and 2500 US$/kW, but on the best sites they can generate power for around 30–40 US$/MWh thanks to low operation, maintenance and fuel costs (Martinot, 2005; NREL, 2005). Costs are very variable, however, due to the diversity of resources on specific sites (Table 4.7). In areas where the industry is growing, many sites with good wind, geothermal, biomass and hydro resources have already been utilized. The less mature technologies are not yet competitive but costs continue to decline due to increased learning experience as exemplified by wind, solar and bioethanol (Figure 4.11). Many renewable energy sources are variable over hourly, daily and/or seasonal time frames. Energy-storage technologies
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Figure 4.11: Investment costs and penetration rates for PV, wind and bioethanol systems showing cost reductions of 20% due to technological development and learning experience for every doubling of capacity once the technology has matured. Source: Johansson et al., 2004.
Proportions of electricity production were calculated using the energy content of the electricity.
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price paid to ethanol producers (US$/m3)
4.3.3
biological hydrogen production involving biomass, algae and bacteria, biorefineries, ocean thermal and saline gradients, and ocean currents.
US$/KW (PV,Wind)
inexhaustible supply of energy with helium as the by-product. The scientific feasibility of fusion energy has been proven, but technical feasibility remains to be demonstrated in experimental facilities. A major international effort, the proposed international thermonuclear experimental reactor (ITER, 2006), aims to demonstrate magnetic containment of sustained, self-heated plasma under fusion temperatures. This 10 billion US$ pilot plant to be built in France is planned to operate for 20 years and will resolve many scientific and engineering challenges. Commercialization of fusion-power production is thought to become viable by about 2050, assuming initial demonstration is successful (Smith et al., 2006a; Cook et al., 2005).
Chapter 4
Chapter 4
may be needed, particularly for wind, wave and solar, though stored hydro reserves, geothermal and bioenergy systems can all be used as dispatchable back-up sources as can thermal power plants. Studies on intermittency and interconnection issues with the grid are ongoing (e.g., Gul and Stenzel, 2005; UKERC, 2006; Outhred and MacGill, 2006). A wide range of policies and measures exist to enhance the deployment of renewable energy (IEA, 2004c; Martinot et al., 2005; Section 4.5). Over 49 nations, including all EU countries along with a number of developing countries such as Brazil, China, Colombia, Egypt, India, Malaysia, Mali, Mexico, Philippines, South Africa and Thailand, and many individual states/provinces of the USA, Canada and Australia have set renewable energy targets. Some targets focus on electricity, while others include renewable heating and cooling and/or biofuels. By 2004, at least 30 states/provinces and two countries had mandates in place for blending bioethanol or biodiesel with petroleum fuels. Since the TAR, several large international companies such as General Electric, Siemens, Shell and BP have invested further in renewable energy along with a wide range of public and private sources. Commercial banks such as Fortis, ANZ Bank and Royal Bank of Canada are financing a growing number of projects; commodity traders and financial investment firms such as Fimat, Goldman Sachs and Morgan Stanley are acquiring renewable energy companies; traditional utilities are developing their own renewable energy projects; commercial reinsurance companies such as Swiss Re and Munich Re are offering insurance products targeting renewable energy, and venture capital investors are observing market projections for wind and PV. New CDM-supported and carbon-finance projects for renewables are emerging and the OECD has improved the terms for Export Credit Arrangements for renewable energy by extending repayment terms (Martinot et al., 2005). There has also been increasing support for renewable energy deployment in developing countries, not only from international development and aid agencies, but also from large and small local financiers with support from donor governments and market facilitators to reduce their risks. As one example, total donor funding pledges or requirements in the Bonn Renewables 2004 Action Programme amounted to around 50 billion US$ (Renewables, 2004). Total investment in new renewable energy capacity in 2005 was 38 billion US$, excluding large hydropower, which itself was another 15–20 billion US$ (Martinot et al., 2006). Numerous detailed and comprehensive reports, websites, and conference proceedings on renewable energy resources, conversion technologies, industry trends and government support policies have been produced since the TAR (e.g., Renewables, 2004; BIREC, 2005; Martinot et al, 2005; IEA, 2004d; IEA, 2005d; IEA 2006a; IEA 2006c; WEC, 2004c; ISES, 2005; WREC, 2006; WREA, 2005). The following
Energy Supply
sections address only the key points relating to progress in each major renewable energy source. 4.3.3.1
Hydroelectricity
Large (>10 MW) hydroelectricity systems accounted for over 2800 TWh of consumer energy in 2004 (BP, 2006) and provided 16% of global electricity (90% of renewable electricity). Hydro projects under construction could increase the share of electricity by about 4.5% on completion (WEC, 2004d) and new projects could be deployed to provide a further 6000 TWh/yr or more of electricity economically (BP, 2004; IEA, 2006a), mainly in developing countries. Repowering existing plants with more powerful and efficient turbine designs can be cost effective whatever the plant scale. Where hydro expansion is occurring, particularly in China and India, major social disruptions, ecological impacts on existing river ecosystems and fisheries and related evaporative water losses are stimulating public opposition. These and environmental concerns may mean that obtaining resource permits is a constraint. Small (<10 MW) and micro (<1 MW) hydropower systems, usually run-of-river schemes, have provided electricity to many rural communities in developing countries such as Nepal. Their present generation output is uncertain with predictions ranging from 4 TWh/yr (WEC, 2004d) to 9% of total hydropower output at 250 TWh/yr (Martinot et al., 2006). The global technical potential of small and micro hydro is around 150–200 GW with many unexploited resource sites available. About 75% of water reservoirs in the world were built for irrigation, flood control and urban water-supply schemes and many could have small hydropower generation retrofits added. Generating costs range from 20 to 90 US$/MWh but with additional costs needed for power connection and distribution. These costs can be prohibitive in remote areas, even for mini-grids, and some form of financial assistance from aid programmes or governments is often necessary. The high level of flexibility of hydro plants enables peak loads in electricity demand to be followed. Some schemes, such as the 12.6 GW Itaipu plant in Brazil/Paraguay, are run as baseload generators with an average capacity factor of >80%, whereas others (as in the 24 GW of pumped storage plant in Japan) are used mainly as fast-response peaking plants, giving a factor closer to 40% capacity. Evaluations of hybrid hydro/ wind systems, hydro/hydrogen systems and low-head run-ofriver systems are under review (IEA, 2006d). GHG emissions vary with reservoir location, power density (W capacity per m2 flooded), flow rate, and whether dam or run-or-river plant. Recently, the GHG footprint of hydropower reservoirs has been questioned (Fearnside, 2004; UNESCO, 2006). Some reservoirs have been shown to absorb CO2 at their surface, but most emit small amounts as water conveys carbon in the natural carbon cycle (Tremblay, 2005). High emissions of CH4 have been recorded at shallow, plateau-type 273
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tropical reservoirs where the natural carbon cycle is most productive (Delmas, 2005). Deep water reservoirs at similar low latitudes tend to exhibit lower emissions. Methane from natural floodplains and wetlands may be suppressed if they are inundated by a new reservoir since the methane is oxidized as it rises through the covering water column (Huttunen, 2005; dos Santos, 2005). Methane formation in freshwater produces by-product carbon compounds (phenolic and humic acids) that effectively sequester the carbon involved (Sikar, 2005). For shallow tropical reservoirs, further research is needed to establish the extent to which these may increase methane emissions. Several Brazilian hydro-reservoirs were compared using life-cycle analyses with combined-cycle natural gas turbine (CCGT) plants of 50% efficiency (dos Santos et al., 2004). Emissions from flooded reservoirs tended to be less per kWh generated than those produced from the CCGT power plants. Large hydropower complexes with greater power density had the best environmental performance, whereas those with lower power density produced similar GHG emissions to the CCGT plants. For most hydro projects, life-cycle assessments have shown low overall net GHG emissions (WEC, 2004a; UNESCO, 2006). Since measuring the incremental anthropogenic-related emissions from freshwater reservoirs remains uncertain, the Executive Board of the UN Framework Convention on Climate Change (UNFCCC) has excluded large hydro projects with significant water storage from the CDM. The IPCC Guidelines for National GHG Inventories (2006) recommended using estimates for induced changes in the carbon stocks. Whether or not large hydro systems bring benefits to the poorest has also been questioned (Collier, 2006; though this argument is not exclusive to hydro). The multiple benefits of hydro-electricity, including irrigation and water-supply resource creation, rapid response to grid-demand fluctuations due to peaks or intermittent renewables, recreational lakes and flood control, need to be taken into account for any given development. Several sustainability guidelines and an assessment protocol have been produced by the industry (IHA, 2006; Hydro Tasmania, 2005; WCD, 2000). 4.3.3.2
Wind
Wind provided around 0.5% of the total 17,408 TWh global electricity production in 2004 (IEA, 2006b) but its technical potential greatly exceeds this (WEC, 2004d; GWEC, 2006). Installed capacity increased from 2.3 GW in 1991 to 59.3 GW at the end of 2005 when it generated 119 TWh at an average capacity factor of around 23%. New wind installation capacity has grown at an average of 28% per year since 2000, with a record 40% increase in 2005 (BTM, 2006) due to lower costs, greater government support through feed-in tariff and renewable energy certificate policies (Section 4.5), and improved technology development. Total offshore wind capacity reached 679 MW at the end of 2005 (BTM, 2006), with the expectation 274
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that it will grow rapidly due to higher mean annual wind-speed conditions offsetting the higher costs and public resistance being less. Various best-practices guidelines have been produced and issues such as noise, electromagnetic (EMF) interference, airline flight paths, land-use, protection of areas with high landscape value, and bird and bat strike, are better understood but remain constraints. Most bird species exhibit an avoidance reaction to wind turbines, which reduces the probability of collision (NERI, 2004). The average size of wind turbines has increased in the last 25 years from less than 50 kW in the early 1980s to the largest commercially available in 2006 at around 5MW and having a rotor diameter of over 120 m. The average turbine size being sold in 2006 was around 1.6–2 MW but there is also a market for smaller turbines <100 kW. In Denmark, wind energy accounted for 18.5% of electricity generation in 2004, and 25% in West Denmark where 2.4 GW is installed, giving the highest generation per capita in the world. Capital costs for land-based wind turbines can be below 900 US$/kW with 25% for the tower and 75% for the rotor and nacelle, although price increases have occurred due to supply shortages and increases in steel prices. Total costs of an onshore wind farm range from 1000–1400 US$/kW, depending on location, road access, proximity to load, etc. Operation and maintenance costs vary from 1% of investment costs in year one, rising to 4.5% after 15 years. This means that on good sites with low surface roughness and capacity factors exceeding 35%, power can be generated for around 30–50 US$/MWh (IEA, 2006c; Morthorst, 2004; Figure 4.12).
0.14
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Figure 4.12: Development of wind-generation costs based on Danish experience since 1985 with variations shown due to land surface and terrain variations (as indicated by roughness indicator classes which equal 0 for open water and up to 3 for rugged terrain). Source: Morthorst, 2004.
Chapter 4
Energy Supply
A global study of 7500 surface stations showed mean annual wind speeds at 80 m above ground exceeded 6.9 m/s with most potential found in Northern Europe along the North Sea, the southern tip of South America, Tasmania, the Great Lakes region, and the northeastern and western coasts of Canada and the US. A technical potential of 72 TW installed global capacity at 20% average capacity factor would generate 126,000 TWh/yr (Archer and Jacobsen, 2005). This is five times the assumed global production of electricity in 2030 (IEA, 2006b) and double the 600 EJ potential capacity estimated by Johansson et al. (2004) (Table 4.2). The main wind-energy investments have been in Europe, Japan, China, USA and India (Wind Force 12, 2005). The Global Wind Energy Council assumed this will change and has estimated more widespread installed capacity of 1250 GW by 2020 to supply 12% of the world’s electricity. The European Wind Energy Association set a target of 75 GW (168 TWh) for EU-15 countries in 2010 and 180 GW (425 TWh) in 2020 (EWEA, 2004). Several Australian and USA states have similar ambitious targets, mainly to meet the increasing demand for power rather than to displace nuclear or fossil-fuel plants. Rapid growth in several developing countries including China, Mexico, Brazil and India is expected since private investment interest is increasing (Martinot et al., 2005). The fluctuating nature of the wind constrains the contribution to total electricity demand in order to maintain system reliability. To supply over 20% would require more accurate forecasting (Giebel, 2005), regulations that ensure wind has priority access to the grid, demand-side response measures, increases in the use of operational reserves in the power system (Gul and Stenzel, 2005) or development of energy storage systems (EWEA, 2005; Mazza and Hammerschlag, 2003). The additional cost burden in Denmark to provide reliability was claimed to be between 1–1.5 billion € (Bendtsen, 2003) and 2–2.5 billion € per annum (Krogsgaard, 2001). However, the costs for back-up power
Biomass Resource
Chapter 7 Industry Food, fibre and wood proces residues
Chapter 4 Energy supply Carbon capture and storage linked with biomass
Bioenergy utilization
Centralised electricity and/or heat generation
Chapter 4 Energy supply
Chapter 8 Agriculture
decrease drastically with larger grid area, larger area containing distributed wind turbines and greater share of flexible hydro and natural-gas-fired power plants (Morthorst, 2004). A trend to replace older and smaller wind turbines with larger, more efficient, quieter and more reliable designs gives higher power outputs from the same site often at a lower density of turbines per hectare. Costs vary widely with location (Table 4.7). Sites with wind speeds of less than 7–8 m/s are not currently economically viable without some form of government support if conventional power-generation costs are above 50 US$/Wh (Oxera, 2005). A number of technologies are under development in order to maximize energy capture for lower wind-speed sites. These include: optimized turbine designs; larger turbines; taller towers; the use of carbon-fibre technology to replace glassreinforced polymer in longer wind-turbine blades; maintenance strategies for offshore turbines to overcome difficulties with access during bad weather/rough seas; more accurate aeroelastic models and more advanced control strategies to keep the wind loads within the turbine design limits. 4.3.3.3
Biomass and bioenergy
Biomass continues to be the world’s major source of food, stock fodder and fibre as well as a renewable resource of hydrocarbons for use as a source of heat, electricity, liquid fuels and chemicals. Woody biomass and straw can be used as materials, which can be recycled for energy at the end of their life. Biomass sources include forest, agricultural and livestock residues, short-rotation forest plantations, dedicated herbaceous energy crops, the organic component of municipal solid waste (MSW), and other organic waste streams. These are used as feedstocks to produce energy carriers in the form of solid fuels (chips, pellets, briquettes, logs), liquid fuels (methanol, ethanol, butanol, biodiesel), gaseous fuels (synthesis gas, biogas, hydrogen), electricity and heat. Biomass resources and bioenergy use are discussed in several other chapters (Fig. 4.13) as outlined
Chapter 9 Forestry
Chapter 10 Waste
Energy and short Forest harvesting and Landfill gas. Other biogas rotation crops. Crop supply chain. Forest MSW incineration and residues. Animal wastes and agroforest residues other thermal processes
Matching biomass supply and demands for bioenergy, biofuels and materials. chapter 4 and chapter 11.
Liquid and gaseous biofuels for transport
Chapter 5 Transport
Heating/electricity and cooking fuels used on side
Chapter 6 Buildings Chapter 7 Industry
Traditional biomass - fuelwood, charcoal and animal dung from agricultural production
Chapter 4 Energy supply Chapter 8 Agriculture Bio-refining, biomaterials, bio-chemicals, charcoal
Chapter 7 Industry
Figure 4.13: Biomass supplies originate from a wide range of sources and, after conversion in many designs of plants from domestic to industrial scales, are converted to useful forms of bioenergy. 275
Energy Supply
in Chapter 11. This chapter 4 concentrates on the conversion technologies of biomass resources to provide bioenergy in the form of heat and electricity to the energy market. Bioenergy carriers range from a simple firewood log to a highly refined gaseous fuel or liquid biofuel. Different biomass products suit different situations and specific objectives for using biomass are affected by the quantity, quality and cost of feedstock available, location of the consumers, type and value of energy services required, and the specific co-products or benefits (IEA Bioenergy, 2005). Prior to conversion, biomass feedstocks tend to have lower energy density per volume or mass compared with equivalent fossil fuels. This makes collection, transport, storage and handling more costly per unit of energy (Sims, 2002). These costs can be minimized if the biomass can be sourced from a location where it is already concentrated, such as wood-processing residues or sugar plant. Globally, biomass currently provides around 46 EJ of bioenergy in the form of combustible biomass and wastes, liquid biofuels, renewable MSW, solid biomass/charcoal, and gaseous fuels. This share is estimated to be over 10% of global primary energy, but with over two thirds consumed in developing countries as traditional biomass for household use (IEA, 2006b). Around 8.6 EJ/yr of modern biomass is used for heat and power generation (Figure 4.14). Conversion is based on inefficient combustion, often combined with significant local and indoor
Chapter 4
air pollution and unsustainable use of biomass resources such as native vegetation (Venkataraman et al., 2004). Residues from industrialized farming, plantation forests and food- and fibre-processing operations that are currently collected worldwide and used in modern bioenergy conversion plants are difficult to quantify but probably supply approximately 6 EJ/yr. They can be classified as primary, secondary and tertiary (Figure 4.15). Current combustion of over 130 Mt of MSW provides more than 1 EJ/yr though this includes plastics, etc. (Chapter 10). Landfill gas also contributes to biomass supply at over 0.2 EJ/yr (Chapter 10). A wide range of conversion technologies is under continuous development to produce bioenergy carriers for both small- and large-scale applications. Organic residues and wastes are often cost-effective feedstocks for bioenergy conversion plants, resulting in niche markets for forest, food processing and other industries. Industrial use of biomass in OECD countries was 5.6 EJ in 2002 (IEA, 2004a), mainly in the form of black liquor in pulp mills, biogas in food processing plants, and bark, sawdust, rice husks etc. in process heat boilers. The use of biomass, particularly sugarcane bagasse, for cogeneration (CHP) and industrial, domestic and district heating continues to expand (Martinot et al., 2005). Combustion for heat and steam generation remains state of the art, but
Figure 4.14: World biomass energy flows (EJ/yr) in 2004 and their thermochemical and biochemical conversion routes to produce heat, electricity and biofuels for use by the major sectors. Note: much of the data is very uncertain, although a useful indication of biomass resource flows and bioenergy outputs still results.
276
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Land-use /
Surface primary prod. 1.5 Gha
land for food/feed crops
Harvest food/feed harvest
Processing
End-use
food processing food consumption
3.5 Gha
pasture land
4.0 Gha
land for forestry/fibre production
animal production
forest harvest
material production
material consumption
Secondary residues Primary residues Tertiary residues land for energy crops 4.2 Gha
other land
energy crop harvest
energy conversion
energy consumption
biomass type and co-firing technology. It is a relatively lowcost, low-risk method of adding biomass capacity, particularly in countries where coal-fired plants are prevalent. Gaseous fuels Gasification of biomass (or coal, Section 4.3.1.1) to synthesis (producer) gas, mainly CO and H2, has a relatively high conversion efficiency (40–45%) when used to generate electricity through a gas engine or gas turbine. The gas produced can also be used as feedstock for a range of liquid biofuels. Development of efficient BIGCC systems is nearing commercial realization, but the challenges of gas clean-up remain. Several pilot and demonstration projects have been evaluated with varying degrees of success (IEA, 2006d).
losses
Figure 4.15: Biomass sources from land used for primary production can be processed for energy with residues available from primary, secondary and tertiary activities. Source: van den Broek, 2000.
advancing technologies include second-generation biofuels (Chapter 5), biomass integrated-gasification combined-cycle (BIGCC), co-firing (with coal or gas), and pyrolysis. Many are close to commercial maturity but awaiting further technical breakthroughs and demonstrations to increase efficiency and further bring down costs. Biochemical conversion using enzymes to convert lignocellulose to sugars that, in turn can be converted to bioethanol, biodiesel, di-methyl ester, hydrogen and chemical intermediates in biorefineries is not yet commercial. Biochemical- and Fischer-Tropsch-based thermochemical synthesis processes can be integrated in a single biorefinery such that the biomass carbohydrate fraction is converted to ethanol and the lignin-rich residue gasified and used to produce heat for process energy, electricity and/or fuels, thus greatly increasing the overall system efficiency to 70–80% (OECD, 2004b; Sims, 2004). Combustion and co-firing Biomass can be combined with fossil-fuel technologies by co-firing solid biomass particles with coal; mixing synthesis gas, landfill gas or biogas with natural gas prior to combustion. There has been rapid progress since the TAR in the development of the co-utilisation of biomass materials in coal-fired boiler plants. Worldwide more than 150 coal-fired power plants in the 50–700 MWe range have operational experience of co-firing with woody biomass or wastes, at least on a trial basis (IEA, 2004c). Commercially significant lignites, bituminous and sub-bituminous coals, anthracites and petroleum coke have all been co-fired up to 15% by energy content with a very wide range of biomass material, including herbaceous and woody materials, wet and dry agricultural residues and energy crops. This experience has shown how the technical risks associated with co-firing in different types of coal-fired power plants can be reduced to an acceptable level through proper selection of
Recovery of methane from anaerobic digestion plants has increased since the TAR. More than 4500 installations (including landfill-gas recovery plants) in Europe, corresponding to 3.3 Mt methane or 92 PJ/yr, were operating in 2002 with a total market potential estimated to be 770 PJ (assuming 28 Mt methane will be produced) in 2020 (Jönsson, 2004). Biogas can be used to produce electricity and/or heat. It can also be fed into natural gas grids or distributed to filling stations for use in dedicated or dual gas-fuelled vehicles, although this requires biogas upgrading (Section 10.4). Costs and reduction opportunities Costs vary widely for biomass fuel sources giving electricity costs commonly between 0.05 and 0.12 US$/kWh (Martinot et al., 2005) or even lower where the disposal cost of the biomass is avoided. Cost reductions can occur due to technical learning and capital/labour substitution. For example, capital investment costs for a high-pressure, direct-gasification combined-cycle plant up to 50 MW are estimated to fall from over 2000 US$/kW to around 1100 US$/kW by 2030, with operating costs, including delivered fuel supply, also declining to give possible generation costs down to 0.03 US$/kWh (Martinot et al., 2005; Specker, 2006; EIA/DOE, 2006). Commercial small-scale options using steam turbines, Stirling engines, organic Rankin-cycle systems etc. can generate power for up to 0.12 US$/kWh, but with the opportunity to further reduce the capital costs by mass production and experience. 4.3.3.4
Geothermal
Geothermal resources from low-enthalpy fields located in sedimentary basins of geologically stable platforms have long been used for direct heat extraction for building and district heating, industrial processing, domestic water and space heating, leisure and balneotherapy applications. High-quality highenthalpy fields (located in geodynamically active regions with high-temperature natural steam reached by drilling at depths less than 2 km) where temperatures are above 250ºC allow for direct electricity production using binary power plants (with low boiling-point transfer fluids and heat exchangers), organic Rankin-cycle systems or steam turbines. Plant capacity factors 277
Energy Supply
range from 40 to 95%, with some therefore suitable for base load (WEC, 2004b). Useful heat and power produced globally is around 2 EJ/yr (Table 4.2). Fields of natural steam are rare. Most are a mixture of steam and hot water requiring single- or double-flash systems to separate out the hot water, which can then be used in binary plants or for direct use of the heat (Martinot et al., 2005). Binary systems have become state-of-the-art technologies but often with additional cost. Re-injection of the fluids maintains a constant pressure in the reservoir and hence increases the life of the field, as well as overcoming any concerns at environmental impacts. Sustainability concerns relating to land subsidence, heat-extraction rates exceeding natural replenishment (Bromley and Currie, 2003), chemical pollution of waterways (e.g. with arsenic), and associated CO2 emissions have resulted in some geothermal power-plant permits being declined. This could be partly overcome by re-injection techniques. Deeper drilling up to 8 km to reach molten rock magma resources may become cost effective in future. Deeper drilling technology could also help to develop widely abundant hot dry rocks where water is injected into artificially fractured rocks and heat extracted as steam. Pilot schemes exist but tend not to be cost effective at this stage. In addition, the growth of ground-to-air heat pumps for heating buildings (Chapter 6) is expected to increase. Capital costs have declined by around 50% from the 3000– 5000 US$/kW in the 1980s for all plant types (with binary cycle plants being the more costly). Power-generation costs vary with high- and low-enthalpy fields, shallow or deep resource, size of field, resource-permit conditions, temperature of resource and the applications for any excess heat (IEA, 2006d; Table 4.7). Operating costs increase if CO2 emissions released either entail a carbon charge or require CCS. Several advanced energy-conversion technologies are becoming available to enhance the use of geothermal heat, including combined-cycle for steam resources, trilateral cycles for binary total-flow resources, remote detection of hot zones during exploration, absorption/regeneration cycles (e.g., heat pumps) and improved power-generation technologies (WEC, 2004c). Improvements in characterizing underground reservoirs, low-cost drilling techniques, more efficient conversion systems and utilization of deeper reservoirs are expected to improve the uptake of geothermal resources as will a decline in the market value for extractable co-products such as silica, zinc, manganese and lithium (IEA, 2006d). 4.3.3.5
Solar thermal electric
The proportion of solar radiation that reaches the Earth’s surface is more than 10,000 times the current annual global energy consumption. Annual surface insolation varies with latitude, ranging between averages of 1000 W/m2 in temperate regions and 1200 W/m2 in low-latitude dry desert areas.
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Concentrating solar power (CSP) plants are categorized according to whether the solar flux is concentrated by parabolic trough-shaped mirror reflectors (30–100 suns concentration), central tower receivers requiring numerous heliostats (500–1000 suns), or parabolic dish-shaped reflectors (1000–10,000 suns). The receivers transfer the solar heat to a working fluid, which, in turn, transfers it to a thermal power-conversion system based on Rankine, Brayton, combined or Stirling cycles. To give a secure and reliable supply with capacity factors at around 50% rising to 70% by 2020 (US DOE, 2005), solar intermittency problems can be overcome by using supplementary energy from associated natural gas, coal or bioenergy systems (IEA, 2006g) as well as by storing surplus heat. Solar thermal power-generating plants are best sited at lower latitudes in areas receiving high levels of direct insolation. In these areas, 1 km2 of land is enough to generate around 125 GWh/yr from a 50 MW plant at 10% conversion of solar energy to electricity (Philibert, 2004). Thus about 1% of the world’s desert areas (240,000 km2), if linked to demand centres by high-voltage DC cables, could, in theory, be sufficient to meet total global electricity demand as forecast out to 2030 (Philibert, 2006; IEA, 2006b). CSP could also be linked with desalination in these regions or used to produce hydrogen fuel or metals. The most mature CSP technology is solar troughs with a maximum peak efficiency of 21% in terms of conversion of direct solar radiation into grid electricity. Tower technology has been successfully demonstrated by two 10 MW systems in the USA with commercial development giving long-term levelized energy costs similar to trough technology. Advanced technologies include troughs with direct steam generation, Fresnel collectors, which can reduce costs by 20%, energy storage including molten salt, integrated combined-cycle systems and advanced Stirling dishes. The latter are arousing renewed interest and could provide opportunities for further cost reductions (WEC, 2004d; IEA 2004b). Technical potential estimates for global CSP vary widely from 630 GWe installed by 2040 (Aringhoff et al., 2003) to 4700 GWe by 2030 (IEA, 2003h; Table 4.2). Installed capacity is 354 MWe from nine plants in California ranging from 14 to 80 MWe with over 2 million m2 of parabolic troughs. Connected to the grid during 1984–1991, these generate around 400 GWh/yr at 100–126 US$/MWh (WEC, 2004d). New projects totalling over 1400 MW are being constructed or planned in 11 countries including Spain (500 MW supported by a new feed-in tariff) (ESTIA, 2004; Martinot et al., 2005) and Israel for the first of several 100 MW plants (Sagie, 2005). The African Development Bank has financed a 50 MW combinedcycle plant in Morocco that will generate 55 GWh/yr, and two new Stirling dish projects totalling 800 MWe planned for the Mojave Desert, USA (ISES, 2005) are estimated to generate at below 90 US$/MWh (Stirling, 2005). Installed capacity of 21.5 GWe, if reached by 2020, would produce 54.6 TWh/yr
Chapter 4
Energy Supply
with a further possible increase leading towards 5% coverage of world electricity demand by 2040. 4.3.3.6
Solar photovoltaic (PV)
Electricity generated directly by utilizing solar photons to create free electrons in a PV cell is estimated to have a technical potential of at least 450,000 TWh/yr (Renewables, 2004; WEC, 2004d). However, realizing this potential will be severely limited by land, energy-storage and investment constraints. Estimates of current global installed peak capacity vary widely, including 2400 MW (Greenpeace, 2004); 3100 MW (Maycock, 2003); >4000MW generating more than 21 TWh (Martinot et al., 2005) and 5000 MW (Greenpeace, 2006). Half the potential may be grid-connected, primarily in Germany, Japan and California, and grow at annual rates of 50–60% in contrast to more modest rates of 15–20% for off-grid PV. Expansion is taking place at around 30% per year in developing countries where around 20% of all new global PV capacity was installed in 2004, mainly in rural areas where grid electricity is either not available or unreliable (WEC, 2004c). Decentralized generation by solar PV is already economically feasible for villages with long distances to a distribution grid and where providing basic lighting and radio is socially desirable. Annual PV module production grew from 740 MW in 2003 to 1700 MW in 2005, with new manufacturing plant capacity built to meet growing demand (Martinot et al., 2005). Japan is the world market leader, producing over half the present annual production (IEA, 2003f). However, solar generation remains at only 0.004% of total world power. Most commercially available solar PV modules are based on crystalline silicon cells with monocrystalline at up to 18% efficiency, having 33.2% of the market share. Polycrystalline cells at up to 15% efficiency are cheaper per Wp (peak Watt) and have 56.3% market share. Modules costing 3–4 US$/Wp can be installed for around 6–7 US$/Wp from which electricity can be generated for around 250 US$/MWh in high sunshine regions (US Climate Change Technology Program, 2005). Cost reductions are expected to continue (UNDP, 2000; Figure 4.11), partly depending on the future world price for silicon; solarcell efficiency improvements as a result of R&D investment; mass production of solar panels and learning through project experience. Costs in new buildings can be reduced where PV systems are designed to be an integral part of the roof, walls or even windows. Thinner cell materials have prospects for cost reduction, including thin-film silicon cells (8.8% of market share in 2003), thin-film copper indium diselenide cells (0.7% of market share), photochemical cells and polymer cells. Commercial thin-film cells have efficiencies up to 8%, but 10–12% should be feasible within the next few years. Experimental multilayer cells have reached higher efficiencies but their cost remains high. Work to reduce the cost of manufacturing, using low-cost polymer materials, and developing new materials such as quantum
dots and nano-structures, could allow the solar resource to be more fully exploited. Combining solar thermal and PV powergeneration systems into one unit has good potential as using the heat produced from cooling the PV cells would make it more efficient (Bakker et al., 2005). 4.3.3.7
Solar heating and cooling
Solar heating and cooling of buildings can reduce conventional fuel consumption and reduce peak electricity loads. Buildings can be designed to use efficient solar collection for passive space heating and cooling (Chapter 6), active heating of water and space using glazed and circulating fluid collectors, and active cooling using absorption chillers or desiccant regeneration (US Climate Change Technology Program, 2003). There is a risk of lower performance due to shading of windows or solar collectors by new building construction or nearby trees. Local ‘shading’ regulations can prevent such conflicts by identifying a protected ‘solar envelope’ (Duncan, 2005). A wide range of design measures, technologies and opportunities are covered by the IEA Solar Heating and Cooling implementing agreement (www.iea-shc.org). Active systems of capturing solar energy for direct heat are used mainly in small-scale, low-temperature, domestic hot water installations; heating of building space; swimming pools; crop drying; cook stoves; industrial processes; desalination plants and solar-assisted district heating. The estimated annual global solar thermal-collector yield of domestic hot water systems alone is around 80 TWh (0.3 EJ) with the installations growing by 20% per year. Annual solar thermal energy use depends on the area of collectors in operation, the solar radiation levels available and the technologies used including both unglazed and glazed systems. Unglazed collectors, mainly used to heat swimming pools in the USA and Europe, represented about 28 million m2 in 2003. More than 130 million m2 of glazed collector area was installed worldwide by the end of 2003 to provide around 0.5 EJ of heat from around 91 GWth capacity (Weiss et al., 2005). In 2005, around 125 million m2 (88 GWth) of active solar hotwater collectors existed, excluding swimming pool heating (Martinot et al, 2005). China is the world’s largest market for glazed domestic solar hot-water systems with 80% of annual global installations and existing capacity of 79 million m2 (55 GWth) at the end of 2005. Most new installations in China are now evacuated-tube in contrast with Europe (the secondlargest market), where most collectors are flat-plate (Zhang et al., 2005). Domestic solar hot-water systems are also expanding rapidly in other developing countries. Estimated annual energy yields for glazed flat-plate collectors range between 400 kWh/m2 in Germany and 1000 kWh/m2 in Israel (IEA, 2004d). In Austria, annual solar yields were estimated to be 300 kWh/m2 for unglazed, 350 kWh/m2 for flat-plate, and 550 kWh/m2 for evacuated tube collectors (Weiss et al., 2005). The retail price for a solar water heater unit for a family home 279
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Chapter 4
differs with location and any government support schemes. Installed costs range from around 700 US$ in Greece for a thermo-siphon system with a 2.4 m2 collector and 150 L tank, to 2300 US$ in Germany for a pumped system with antifreeze device. Systems manufactured in China are typically 200– 300 US$ each.
coastline exceeds 30 kW/m, giving a technical potential of around 500 GW assuming offshore wave-energy devices have 40% efficiency. The total economic potential is estimated to be well below this (WEC, 2004d) with generating cost estimates around 80–110 US$/MWh highly uncertain, since no truly commercial scale plant exists (IEA, 2006d).
Nearly 100 commercial solar cooling technologies exist in Europe, representing 24,000 m2 with a cooling power of 9 MWth. High potential energy savings compared with conventional electric vapour-pressure air-conditioning systems do not offset the higher costs (Philibert and Podkanski, 2005).
Extracting electrical energy from marine currents could yield in excess of 10 TWh/yr (0.4 EJ/yr) if major estuaries with large tidal fluctuations could be tapped, but cost estimates range from 450–1350 US$/MWh (IEA, 2006a). A 1 km-stretch of permanent turbines built in the Agulhas current off the coast of South Africa, for example, could give 100 MW of power (Nel, 2003). However, environmental effects on tidal mud flats, wading birds, invertebrates etc. would need careful analysis. In order for these new technologies to enter the market, sustained government and public support is needed.
4.3.3.8
Ocean energy
The potential marine-energy resource of wind-driven waves, gravitational tidal ranges, thermal gradients between warm surface water and colder water at depths of >1000 m, salinity gradients, and marine currents is huge (Renewables, 2004), but what is exploitable as the economic potential is low. All the related technologies (with the exception of three tidalrange barrages amounting to 260 MW, including La Rance that has generated 600 GWh/yr since 1967) are at an early stage of development with the only two commercial wave-power projects totalling 750 kW. To combat the harsh environment, installed costs are usually high. The marine-energy industry is now in a similar stage of development to the wind industry in the 1980s (Carbon Trust, 2005). Since oceans are used by a range of stakeholders, siting devices will involve considerable consultation.
Ocean thermal and saline gradient energy-conversion systems remain in the research stage and it is still too early to estimate their technical potential. Initial applications have been for building air conditioning (www.makai.com/p-pipelines/) for desalination in open- and hybrid-cycle plants using surface condensers and in future could benefit tropical island nations where power is presently provided by expensive diesel generators. 4.3.4
Energy carriers include electricity and heat as well as solid, liquid and gaseous fuels. They occupy intermediate steps in the energy-supply chain between primary sources and end-use applications. An energy carrier is thus a transmitter of energy. For reasons of both convenience and economy, energy carriers
The best wave-energy climates (Figure 4.16) have deepwater power densities of 60–70 kW/m but fall to about 20 kW/m at the foreshore. Around 2% of the world’s 800,000 km of
57
33 27 24 29 40 29 50 29 45 29 33 82 92 6263 EUROPE 65 48
49 40
64 49 41 38
NORTH AMERICA
49 33 24
15
12
AFRICA
10 13 20 24
SOUTH AMERICA
50 74
34 14
17
11
12 40
15 18
21
33 29 97
Figure 4.16: Annual average wave-power density flux (kW/m at deep water)
26
38 23
25
36 40
17
19
18
11 16
13
13
26
13
280
63 41
ASIA 17
14
Source: Wavegen, 2004.
Energy carriers
50
40 82 76
AUSTRALIA
Chapter 4
Energy Supply
have shown a continual shift from solids to liquids and more recently from liquids to gases (WEC, 2004b), a trend that is expected to continue. At present, about one third of final energy carriers reach consumers in solid form (as coal and biomass, which are the primary cause of many local, regional and indoor air-pollution problems associated with traditional domestic uses); one third in liquid form (consisting primarily of oil products used in transportation); and one third through distribution grids in the form of electricity and gas. The share of all grid-oriented energy carriers could increase to about one half of all consumer energy by 2100. New energy carriers such as hydrogen (Section 4.3.4.3) will only begin to make an impact around 2050, whereas the development of smaller scale decentralized energy systems and micro-grids (Section 4.3.8) could occur much sooner (Datta et al., 2002; IEA, 2004d). Technology issues surrounding energy carriers involve the conversion of primary to secondary energy, transporting the secondary energy, in some cases storing it prior to use, and converting it to useful end-use applications (Figure 4.17). Where a conversion process transforms primary energy near the source of production (e.g. passive solar heating) a carrier is not involved. In other cases, such as natural gas or woody
biomass, the primary-energy source also becomes the carrier and also stores the energy. Over long distances, the primary transportation technologies for gaseous and liquid materials are pipelines, shipping tankers and road tankers; for solids they are rail wagons, boats and trucks, and for electricity wire conductors. Heat can also be stored but is normally transmitted over only short distances of 1–2 km. Each energy-conversion step in the supply chain invokes additional costs for capital investment in equipment, energy losses and carbon emissions. These directly affect the ability of an energy path to compete in the marketplace. The final benefit/ cost calculus ultimately determines market penetration of an energy carrier and hence the associated energy source and enduse technology. Hydrocarbon substances produced from fossil fuels and biomass are utilized widely as energy carriers in solid, slurry, liquid or gaseous forms (Table 4.3). Coal, oil, natural gas and biomass can be used to produce a variety of synthetic liquids and gases for transport fuels, industrial processes and domestic heating and cooking, including petroleum products refined from crude oil. Liquid hydrocarbons have relatively high energy densities that are superior for transport and storage properties.
- Accessibility - Availability - Acceptability
End-uses industry, metallurgy/chemicals/pulp & paper households, heat/lighting/appliances traffic, car/heavy/public/rail/sea/air
Carriers
electricity heat
liquid fuels gasoline/diesel/kerosene ethanol, methanol crude oil natural gas coal peat biomass, residues & waste bioproducts, cultivated hydro wind solar radiation nuclear
natural gas hydrogen
gases
coal, peat, wood chips & pellets solid fuels
Convenience, cost, and efficiency (Accessibility) Quality, reliability (Availability) Emissions (Acceptability)
Sources
Figure 4.17: Dynamic interplay between energy sources, energy carriers and energy end-uses. Energy sources are shown at the lower left; carriers in the middle; and end-uses at the upper right. Important intersections are noted with circles, small blue for transformations to solid energy carriers and small pink to liquid or gaseous carriers. Large green circles are critical transformations for future energy systems. Source: WEC, 2004d.
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Table 4.3: Energy carriers of hydrocarbon substances. Energy carriers of secondary energy Primary energy
Solid
Slurry
Coal
Pulverized coal Coke
Liquid Coal to liquid (CTL) Synthetic fuel
Coal gas Producer gas Blast furnace gas Water gas Gasified fuel Hydrogen
Oil
Oil refinery products
Oil gas Synthetic gas Hydrogen
Natural gas
LNG, LPG Gas to liquid (GTL) GTL alcoholics Di-methyl ethers
Methane Hydrogen
Methanol Ethanol Biodiesel esters Di-methyl ethers
Methane Producer gas Hydrogen
Biomass
4.3.4.1
Coal/water mix Coal/oil mix
Gas
Wood residues Energy crops Refuse derived fuel (RDF)
Electricity
Electricity is the highest-value energy carrier because it is clean at the point of use and has so many end-use applications to enhance personal and economic productivity. It is effective as a source of motive power (motors), lighting, heating and cooling and as the prerequisite for electronics and computer systems. Electricity is growing faster as a share of energy enduses (Figure 4.18) than other direct-combustion uses of fuels with the result that electricity intensity (Electricity/GDP) has remained relatively constant even though the overall globalenergy intensity (Energy/GDP) continues to decrease. If electricity intensity continues to decrease due to efficiency increases, future electricity demand could be lower than otherwise forecast (Sections 4.4.4 and 11.3.1).
Life-cycle GHG-emission analyses of power-generation plants (WEC 2004a; Vattenfall, 2005; Dones et al., 2005; van de Vate, 2002; Spadaro, 2000; Uchiyama and Yamamoto, 1995; Hondo, 2005) show the relatively high CO2 emissions from fossil-fuel combustion are 10–20 times higher than the indirect emissions associated with the total energy requirements for plant construction and operation during the plant’s life (Figure 4.19). Substitution by nuclear or renewable energy decreases carbon emissions per kWh by the difference between the fullenergy-chain emission coefficients and allowing for varying plant-capacity factors (WEC 2004a; Sims et al., 2003a). The average thermal efficiency for electricity-generation plants has improved from 30% in 1990 to 36% in 2002, thereby reducing GHG emissions. Electricity generated from traditional coal-fired, steampower plants is expected to be displaced over time with more advanced technologies such as CCGT or advanced coal to reduce the production of GHG and increase the overall efficiency of energy use. Previous IPCC (2001) and WEC (2001) scenarios suggested that nuclear, CCGT and CCS could become dominant electricity-sector technologies early this century (Section 4.4). Although CCS can play a role, its potential may be limited and hence some consider it as a transitional bridging technology.
Electricity/total energy 0.45 0.40 0.35 0.30 0.25 0.20 0.15
4.3.4.2
Heat and heat pumps
0.10 0.05 0 1880
1900
1920
1950
1960
1980
2000
2020
year Figure 4.18: Ratio of electricity to total primary energy in the US since 1900. Source: EPRI, 2003.
282
Heat, whether from fossil fuels or renewable energy, is a critical energy source for all economies. Its efficient use could play an important role in the development of transition and developing economies (UN, 2004; IEA, 2004e). It is used in industrial processes for food processing, petroleum refining, timber drying, pulp production, etc. (Chapter 7), as well as in commercial and residential buildings for space heating, hot
Chapter 4
Energy Supply
4.3.4.3
tonnes CO2-eq/GWhel 0
200
400
600
800
1000
1200
Lignite FGD, high FGD, low FGD, high FGD, low
Coal
with CCS low-NOx combined cycle
Heavy fuel oil
high low
Natural gas, combined cycle
SCR with CCS high low
Photovoltaic
high low
Hydro
IGCC, high IGCC, low
Liquid and gaseous fuels
1400
stack emissions other stages
Tree plantation
Coal, natural gas, petroleum and biomass can all be used to produce a variety of liquid fuels for transport, industrial processes, power generation and, in some regions of the world, domestic heating. These include petroleum products from crude oil or coal; methanol from coal or natural gas; ethanol and fatty acid esters (biodiesel) from biomass; liquefied natural gas; and synthetic diesel fuel and di-methyl ether from coal or biomass. Of these, crude oil is the most energy-efficient fuel to transport over long distances from source to refinery and then to distribute to product demand points. After petrol, diesel oil and other light and medium distillates are extracted at the refinery, the residues are used to produce bitumen and heavy fuel oil used as an energy source for industrial processes, oil-fired power plants and shipping. Gaseous fuels provide a great deal of the heating requirements in the developed world and increased use can lead to lower GHG and air-pollution emissions.
offshore, high offshore, low onshore, high onshore, low high low
Wind
Nuclear
Figure 4.19: GHG emissions for alternative electricity-generation systems. Notes: 1 tCO2 –eq/GWh = 0.27 tC –eq/GWh. The high estimate for hydro includes possible GHG emissions from reservoirs (Section 4.3.3.1) Source: WEC, 2004a
water and cooking (Chapter 6). Many industries cogenerate both heat and electricity as an integral part of their production process (Section 4.3.5; Chapter 7), in most cases being used on-site, but at times sold for other uses off-site such as district heating schemes. Heating and cooling using renewable energy (Section 4.3.3.7) can compete with fossil fuels (IEA, 2006f). In some instances, the best use of modern biomass will be co-firing with coal at blends up to 5–10% biomass or with natural gas.
Hydrogen Realizing hydrogen as an energy carrier depends on low-cost, high-efficiency methods for production, transport and storage. Most commercial hydrogen production today is based on steam reforming of methane, but electrolysis of water (especially using carbon-free electricity from renewable or nuclear energy) or splitting water thermo-chemically may be viable approaches in the future. Electrolysis may be favoured by development of fuel cells that require a low level of impurities. Current costs of electrolysers are high but declining. Producing hydrogen from fossil fuels on a large scale will need integration of CCS if GHG emissions are to be avoided. A number of routes to produce hydrogen from solar energy are also technically feasible (Figure 4.20). Hydrogen has potential as an energy-storage medium for electricity production or transport fuel when needed. The prospects for a future hydrogen economy will depend
SOLAR ENERGY
Heat pumps can be used for simple air-to-air space heating, air-to-water heating, and for utilizing waste heat in domestic, commercial and industrial applications (Chapter 6). Thermodynamically reverse Carnot-cycle heat pumps are more demandside technologies but also linked with sustainable energy supply by concentrating low-grade solar heat in air and water. Their efficiency is evaluated by the coefficient of performance (COP), with COPs of 3 to 4 available commercially and over 6 using advanced turbo-refrigeration (www.mhi.co.jp/aircon/). A combination of CCGT with advanced heat-pump technology could reduce carbon emissions from supplying heat more than using a conventional gas-fired CHP plant of similar capacity.
heat
biomass
conversion
mechanical energy electricity thermolysis
electrolysis
photolysis
HYDROGEN Figure 4.20: Routes to hydrogen-energy carriers from solar-energy sources. Source: EPRI, 2003
283
Energy Supply
Chapter 4
4.3.5
Combined heat and power (CHP)
Up to two thirds of the primary energy used to generate electricity in conventional thermal power plants is lost in the form of heat. Switching from condensing steam turbines to CHP (cogeneration) plants produces electricity but captures the excess heat for use by municipalities for district heating, commercial buildings (Chapter 6) or industrial processes (Chapter 7). CHP is usually implemented as a distributed energy resource (Jimison, 2004), the heat energy usually coming from steam turbines and internal combustion engines. Current CHP designs can boost overall conversion efficiencies to over 80%, leading to cost savings (Table 4.4) and hence to significant carbon-emissions reductions per kWh generated. About 75% of district heat in Finland, for example, is provided from CHP plants with typical overall annual efficiencies of 85–90% (Helynen, 2005). CHP plants can range from less than 5 kWe from micro-gasturbines, fuel cells, gasifiers and Stirling engines (Whispergen, 2005) to 500 MWe. A wide variety of fuels is possible including
100 CO2 emissions Efficiency
80
600
60
400
40
200
20 0
tio n st al c ea o m alNe tu fire rb d w in cle e st an c ea o a m tu l-fire rb d Co in e al ga s ga i f i s ca Ne tu tio rb n ga w c in s om e tu b rb in in ed e (C -cyc CG le T) CH P co al -fi re d CH P ga sfir ed
0
Efficiency
CO2-emissions
800
di
Hydrogen fuel cells may eventually become commercially viable electricity generators, but because of current costs, complexity and state of development, they may only begin to penetrate the market later this century (IEA, 2005g). Ultimately, hydrogen fuel could be produced in association with CCS leading to low-emission transport fuels. Multi-fuel integratedenergy systems or ‘energyplexes’ (Yamashita and Barreto, 2005) could co-produce electricity, hydrogen and liquid fuels with overall high-conversion efficiencies, low emissions and also facilitating CCS. FutureGen is a US initiative to build the world’s first integrated CCS and hydrogen-production research power plant (US DOE, 2004).
%
kg CO2/MWh 1000
Tr a
on developing competitively priced fuel cells for stationary applications or vehicles, but fuel cells are unlikely to become fully commercial for one or two decades. International cooperative programmes, such as the IEA Hydrogen Implementing Agreement (IEA, 2005f), and more recently the International Partnership for the Hydrogen Economy (www. iphe.net) aim to advance RD&D on hydrogen and fuel cells across the application spectrum (IEA, 2003g; EERE, 2005).
Figure 4.21: Carbon dioxide emissions and conversion efficiencies of selected coal and gas-fired power generation and CHP plants. Note: CHP coal- fired and CHP gas-fired assume more of the available heat is utilized from coal than from gas to both give 80%.
biomass (Kirjavainen et al., 2004), with individual installations accepting more than one fuel. A well-designed and operated CHP scheme will provide better energy efficiency than a conventional plant, leading to both energy and cost savings (UNEP, 2004; EDUCOGEN, 2001). Besides the advantage of cost reductions because of higher efficiency, CHP has the environmental benefit of reducing 160–500 gCO2/kWh, given a fossil-fuel baseline for the heat and electricity generation. 4.3.6
Carbon dioxide capture and storage (CCS)
The potential to separate CO2 from point sources, transport it and store it in isolation from the atmosphere was covered in an IPCC Special Report (IPCC, 2005). Uncertainties relate to proving the technologies, anticipating environmental impacts and how governments should incentivise uptake, possibly by regulation (OECD/IEA, 2005) or by carbon charges, setting a price on carbon emissions. Capture of CO2 can best be applied
Table 4.4: Characteristics of CHP (cogeneration) plants Capacity MW
Electrical efficiency (%)
Overall efficiency (%)
Any combustible
0.5-500
17-35
60-80
Gas turbine
Gasous & liquid
0.25-50+
25-42
65-87
Combined cycle
Gasous & liquid
3-300+
35-55
73-90
Diesel and Otto engines
Gasous & liquid
0.003-20
25-45
65-92
Micro-turbines
Gasous & liquid
0.05-0.5
15-30
60-85
Fuel cells
Gasous & liquid
0.003-3+
37-50
85-90
Stirling engines
Gasous & liquid
0.003-1.5
30-40
65-85
Technology
Fuel
Steam turbine
284
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to large carbon point sources including coal-, gas- or biomassfired electric power-generation or cogeneration (CHP) facilities, major energy-using industries, synthetic fuel plants, natural gas fields and chemical facilities for producing hydrogen, ammonia, cement and coke. Potential storage methods include injection into underground geological formations, in the deep ocean or industrial fixation as inorganic carbonates (Figure 4.22). Application of CCS for biomass sources (such as when co-fired with coal) could result in the net removal of CO2 from the atmosphere.
Other studies show a more rapid deployment starting around the same time, but with continuous expansion even towards the end of the century (IPCC, 2005). Yet other studies show no significant use of CCS until 2050, relying more on energy efficiency and renewable energy (IPCC, 2005). Long-term analyses by use of integrated assessment models, although using a simplified carbon cycle (Read and Lermit, 2005; Smith, 2006b), indicated that a combination of bioenergy technologies together with CCS could decrease costs and increase attainability of low stabilization levels (below 450 ppmv).
Injection of CO2 in suitable geological reservoirs could lead to permanent storage of CO2. Geological storage is the most mature of the storage methods, with a number of commercial projects in operation. Ocean storage, however, is in the research phase and will not retain CO2 permanently as the CO2 will re-equilibrate with the atmosphere over the course of several centuries. Industrial fixation through the formation of mineral carbonates requires a large amount of energy and costs are high. Significant technological breakthroughs will be needed before deployment can be considered.
New power plants built today could be designed and located to be CCS-ready if rapid deployment is desired (Gibbins et al., 2006). All types of power plants can be made CCS-ready, although the costs and technical measures vary between different types of power plants. However, beyond space reservation for the capture, installation and siting of the plant to enable access to storage reservoirs, significant capital pre-investments at build time do not appear to be justified by the cost reductions that can be achieved (Bohm, 2006; Sekar, 2005). Although generic outline engineering studies for retro-fitting capture technologies to natural-gas GTCC plants have been undertaken, detailed reports on CCS-ready plant-design studies are not yet in the public domain.
Estimates of the role CCS will play over the course of the century to reduce GHG emissions vary. It has been seen as a ‘transitional technology’, with deployment anticipated from 2015 onwards, peaking after 2050 as existing heat and powerplant stock is turned over, and declining thereafter as the decarbonization of energy sources progresses (IEA, 2006a).
Storage of CO2 can be achieved in deep saline formations, oil and gas reservoirs and deep unminable coal seams using injection and monitoring techniques similar to those utilized by
Figure 4.22: CCS systems showing the carbon sources for which CCS might be relevant, and options for the transport and storage of CO2. Source: IPCC, 2005.
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Energy Supply
the oil and gas industry. Of the different types of potential storage formations, storage in coal formations is the least developed. If injected into suitable saline formations or into oil and gas fields at depths below 800 m, various physical and geochemical trapping mechanisms prevent the CO2 from migrating to the surface. Projects in all kinds of reservoirs are planned. Storage capacity in oil and gas fields, saline formations and coal beds is uncertain. The IPCC (IPCC, 2005) reported 675 to 900 GtCO2 for the relatively well-characterized gas and oil fields, more than 1000 GtCO2 (possibly up to an order of magnitude higher) for saline formations, and up to 200 GtCO2 for coal beds. Bradshaw et al. (2006) highlighted the incomparability of localized storage-capacity data that use different assumptions and methodologies. They also criticized any top-down estimate of storage capacity not based on a detailed site characterization and a clear methodology, and emphasized the value of conservative estimates. In the literature, however, specific estimates were based on top-down data and varied beyond the range cited in the IPCC (2005). For instance, a potential of >4000 GtCO2 was reported for saline formations in North America alone (Dooley et al., 2005) and between 560 and 1170 GtCO2 for injection in oil and gas fields (Plouchart et al., 2006). Agreement on a common methodology for storage capacity estimates on the country- and region-level is needed to give a more reliable estimate of storage capacities. Biological removal of CO2 from an exhaust stream is possible by passing the stack emissions through an algae or bacterial solution in sunlight. Removal rates of 80% for CO2 and 86% for NOX have been reported, resulting in the production of 130,000 litres/ha/yr of biodiesel (Greenfuels 2004) with residues utilized as animal feed. Other unconventional biological approaches to CCS or fuel production have been reported (Greenshift, 2005; Patrinos, 2006). Another possibility is the capture of CO2 from air. Studies claim costs less than 75 US$/tCO2 and energy requirements of a minimum of 30% using a recovery cycle with Ca(OH)2 as a sorbent. However, no experimental data on the complete process are yet available to demonstrate the concept, its energy use and engineering costs. Before the option of ocean injection can be deployed, significant research is needed into its potential biological impacts to clarify the nature and scope of environmental consequences, especially in the longer term (IPCC, 2005). Concerns surrounding geological storage include the risk of seismic activity causing a rapid release of CO2 and the impact of old and poorly sealed well bores on the storage integrity of depleted oil and gas fields. Risks in CO2 transportation include rupture or leaking of pipelines, possibly leading to the accumulation of a dangerous level of CO2 in the air. Dry CO2 is not corrosive to pipelines even if it contains contaminants, but it becomes corrosive when moisture is present. Any moisture therefore needs to be removed to prevent corrosion and avoid the high cost of constructing pipes made from corrosionresistant material. Transport of CO2 by ship is feasible under 286
Chapter 4
specific conditions, but is currently carried out only on a small scale due to limited demand (IPCC, 2005). Clarification of the nature and scope of long-term environmental consequences of ocean storage requires further research (IPCC, 2005). Concerns around geological storage include rapid release of CO2 as a consequence of seismic activity and the impact of old and poorly sealed well bores on the storage integrity of depleted oil and gas fields Risks are estimated to be comparable to those of similar operations (IPCC, 2005). For CO2 pipelines, accident numbers reported are very low, although there are risks of rupture or leaking leading to local accumulation of CO2 in the air to dangerous levels (IPCC, 2005). 4.3.6.1
Costs
Cost estimates of the components of a CCS system vary widely depending on the base case and the wide range of source, transport and storage options (Table 4.5). In most systems, the cost of capture (including compression) is the largest component, but this could be reduced by 20–30% over the next few decades using technologies still in the research phase as well as by upscaling and learning from experience (IPCC, 2005). The extra energy required is a further cost consideration. CO2 storage is economically feasible under conditions specific to enhanced oil recovery (EOR), and in saline formations, avoiding carbon tax charges for offshore gas fields in Norway. Pipeline transport of CO2 operates as a mature market technology (IPCC, 2005), costing 1–5 US$/tCO2 per 100 km (high end for very large volumes) (IEA, 2006a). Several thousand kilometres of pipelines already transport 40 Mt/yr of CO2 to EOR projects. The costs of transport and storage of CO2 could decrease slowly as technology matures further and the plant scale increases. 4.3.7
Transmission, distribution, and storage
A critical requirement for providing energy at locations where it is converted into useful services is a system to move the converted energy (e.g. refined products, electricity, heat) and store it ready for meeting a demand. Any leakage or losses (Figure 4.23) result in increased GHG emissions per unit of useful consumer energy delivered as well as lost revenue. Electricity transmission networks cover hundreds of kilometres and have successfully provided the vital supply chain link between generators and consumers for decades. The fundamental architecture of these networks has been developed to meet the needs of large, predominantly fossil fuel-based generation technologies, often located remotely from demand centres and hence requiring transmission over long distances to provide consumers with energy services. Transmission and distribution networks account for 54% of the global capital assets of electric power (IEA, 2004d). Aging equipment, network congestion and extreme peak load
Chapter 4
Energy Supply
Table 4.5: Current cost ranges for the components of a CCS system applied to a given type of power plant or industrial source CCS system components
Cost range
Remarks
Capture from a coal- or gas-fired power plant
15-75 US$/tCO2 net captured
Net costs of captured CO2 compared to the same plant without capture
Capture from hydrogen and ammonia production or gas processing
5-55 US$/tCO2 net captured
Applies to high-purity sources requiring simple drying and compression
Capture from other industrial sources
25-115 US$/tCO2 net captured
Range reflects use of a number of different technologies and fuels
Transport
1-8 US$/tCO2 transported
Per 250 km pipeline or shipping for mass flow rates of 5 (high end) to 40 (low end) MtCO2/yr.
Geological storagea
0.5-8 US$/tCO2 net injected
Excluding potential revenues from EOR or ECBM.
Geological storage: monitoring and verification
0.1-0.3 US$/tCO2 injected
This covers pre-injection, injection, and post-injection monitoring, and depends on the regulatory requirements
Ocean storage
5-30 US$/tCO2 net injected
Including offshore transportation of 100–500 km, excluding monitoring and verification
Mineral carbonation
50-100 US$/tCO2 net mineralized
Range for the best case studied. Includes additional energy use for carbonation
a Over the long term, there may be additional costs for remediation and liabilities Source: IPCC, 2005.
demands contribute to losses and low reliability, especially in developing countries, such that substantial upgrading is often required. Existing infrastructure will need to be modernized to improve security, information and controls, and to incorporate low-emission energy systems. Future infrastructure and control systems will need to become more complex in order to handle higher, more variable loads; to recognize and dispatch smallscale generators; and to enable the integration of intermittent and decentralized sources without reduced system performance as it relates to higher load flow, frequency oscillations, and
Oil LNG-steam turbine LNG-combined cycle Coal-steam turbine
Net electricity T&D losses Indirect losses Conversion loss
Coal-super critical steam turbine Goal-IGCC Nuclear-gas diffusion enrichment
voltage quality (IEA, 2006a). New networks being built should have these features incorporated, though due to private investors seeking to minimize investment costs, this is rarely the case. The demands of future systems may be significantly less than might be otherwise anticipated through increased use of distributed energy (IEA, 2003c). Superconducting cables, sensors and rapid response controls that could help to reduce electricity costs and line losses are all under development. Superconductors may incorporate hydrogen as both cryogenic coolant and energy carrier. System management will be improved by providing advanced information on grid behaviour; incorporating devices to route current flows on the grid; introduce real-time pricing and other demand-side technologies including smart meters and better system planning. The energy security challenges that many OECD countries currently face from technical failures, theft, physical threats to infrastructure and geopolitical actions are concerns that can be overcome in part by greater deployment of distributed energy systems to change the electricity-generation landscape (IEA, 2006g). 4.3.7.1
Nuclear-centrifugal enrichment Biomass-IGCC Geothermal 0
500 1000 1500 2000 2500 3000 3500 4000
Net electricity and energy losses (PJ) Figure 4.23: Comparison of net electricity production per 1000MWe of installed capacity for a range of power-generation technology systems in Japan. Note: Analysed over a 30-year plant life, and showing primary fuel-use efficiency losses and transmission losses assuming greater distances for larger scale plants. Transport and distribution losses were taken as 4% for fossil fuel and bioenergy, 7% for nuclear. Source: Data updated from Uchiyama, 1996.
Energy storage
Energy storage allows the energy-supply system to operate more or less independently from the energy-demand system. It addresses four major needs: utilizing energy supplies when short-term demand does not exist; responding to short-term fluctuations in demand (stationary or mobile); recovering wasted energy (e.g. braking in mobile applications), and meeting stationary transmission expansion requirements (Testor et al., 2005). Storage is of critical importance if variable low-carbon energy options such as wind and solar are to be better utilized, and if existing thermal or nuclear systems are 287
Energy Supply
to be optimized for peak performance in terms of efficiencies and thus emissions. Advanced energy-storage systems include mechanical (flywheels, pneumatic), electrochemical (advanced batteries, reversible fuel cells, hydrogen), purely electric or magnetic (super- and ultra-capacitors, superconducting magnetic storage), pumped-water (hydro) storage, thermal (heat) and compressed air. Adding any of these storage systems necessarily decreases the energy efficiency of the entire system (WEC, 2004d). Overall, cycle efficiencies today range from 60% for pumped hydro to over 90% for flywheels and supercapacitors (Testor et al., 2005). Electric charge carriers such as vanadium redox batteries and capacitors are under evaluation but have low energy density and high cost. Cost and durability (cycle life) of the high-technology systems remains the big challenge, possibly to be met by more advanced materials and fabrication. Energy storage has a key role for small local systems where reliability is an important feature. 4.3.8
Decentralized energy
Decentralized (or distributed) energy systems (DES) located close to customer loads often employ small- to medium-scale facilities to provide multiple-energy services referred to as ‘polygeneration’. Grid-connected DES are already commercial in both densely populated urban markets requiring supply reliability and peak shedding as well as in the form of minigrids in rural markets with high grid connection costs and abundant renewable energy resources. Diesel-generating sets are an option, but will generally emit more CO2 per kWh than a power grid system. Renewable-energy systems connected to the grid or used instead of diesel gensets will reduce GHG emissions. The merits of DES include: • reduced need for costly transmission systems and shorter times to bring on-stream; • substantially reduced grid power losses over long transmission distances resulting in deferred costs for upgrading transmission and distribution infrastructure capacity to meet a growing load; • improved reliability of industrial parks, information technology and data management systems including stock markets, banks and credit card providers where outages would prove to be very costly (IEA, 2006g); • proximity to demand for heating and cooling systems which, for fossil fuels, can increase the total energy recovered from 40–50% up to 70–85% with corresponding reductions in CO2 emissions of 50% or more; • zero-carbon, renewable energy sources such as solar, wind and biomass are widely distributed and useful resources for DES. However, developing decentralized mini-power grids is usual practice if these sources are to make significant local contributions to electricity supply and emission reductions. There are added expenses, power limitations and reliability issues with DES. The World Alliance for Decentralized Energy 288
Chapter 4
(WADE, 2005) reported that at the end of 2004, just 7.2% of global electric power generation was supplied by decentralized systems, having a total capacity of 281.9 GWe. Capacity of DES expanded by 11.4% between 2002 and 2004, much of it as combined heat and power (CHP) using natural gas or biomass to combine electric power generation with the capture and use of waste heat for space heating, industrial and residential hot water, or for cooling. Growth in the USA, where capacity stands at 80 GWe, has been relatively slow because of regulatory barriers and the rising price of natural gas. The European market is expected to expand following the 2003 Cogeneration Directive from the European Commission, while India has added decentralized generation to enhance system reliability. Brazil, Australia and elsewhere are adding CHP facilities that use bagasse from their sugar and ethanol processing. Brazil has the potential to generate 11% of its electricity from this source. China is also adding small amounts of decentralized electric power in some of its major cities (50 GWe in 2004), but central power still dominates. Japan is promoting the use of natural gas-fuelled CHP with a target of almost 5000 MW by 2010 to save over 11 MtCO2 (Kantei, 2006). In 2005, 24% of global electricity markets from all newly installed power plants were claimed to be from DES (WADE, 2006). The trend towards DES is growing, especially for distributed electricity generation (DG), in which local energy sources (often renewable) are utilized or energy is carried as a fuel to a point at or near the location of consumption where it is then converted to electricity and distributed locally. As well as wind, geothermal and biomass-fuelled technologies, DG systems can use a wide range of fuels to run diesel generators, gas engines, small and micro-turbines, and Stirling engines with power outputs down to <1 kWe and widely varying power-heat output ratios between 1:3 and 1:36 (IEA, 2006a). The motive power of a vehicle to supply electricity could be used. Hydrogen (Section 4.3.4.3), could fuel modified internal combustion engines to provide a near-term option, or fuel cells in the longer term (Gehl, 2004). A critical objective, however, will be to first increase the power density of fuel cells, reduce the installed costs and store the hydrogen safely. Small-to-medium CHP systems at a scale of 1–40 MWe are in common use as the heat can be usefully employed on site or locally. CCS systems will probably not be economic at such a small scale. Mass production of technologies as demand increases will help reduce the current high costs of around 5000 US$/kWe for many small systems. Reciprocating engine generator sets are commercially available; micro CHP Stirling engine systems are close to market (Whispergen, 2005) and fuel cells with the highest power-heat ratio need significant capital cost reductions. The recent growth in DG technologies, mainly dieselgeneration based, to provide reliable back-up systems, is apparent in North America (Figure 4.24). Technology advances
Chapter 4
Energy Supply
on site to provide process heat and power. This is covered in Chapter 7.
GW
8 7
Reciprocating engines Gas turbines
6
4.4 Mitigation costs and potentials of energy supply
5 4
estimate
3 2 1
89
-9 0 90 -9 91 1 -9 2 92 -9 3 93 -9 4 94 -9 5 95 -9 6 96 -9 7 97 -9 8 98 -9 9 99 -0 0 00 -0 01 1 -0 2 02 -0 3 03 -0 4
0
years Figure 4.24: Recent growth in distributed electricity generation using fossil-fuel resources in North America. Source: EPRI, 2003.
may encourage the emergence of a new generation of highervalue energy services, including power quality and informationrelated services based on fuel cells with good reliability. Flexible alternating-current transmission systems (FACTS) are now being employed as components using information technology (IT) and solid-state electronics to control power flow. Numerous generators can then be controlled by the utility or line company to match the ever-changing load demand. Improved grid stability can result from appliances such as cool stores shedding load and generation plants starting up in response to system frequency variations. In addition, price sensitivities and real-time metering could be used to stimulate selected appliances to be used off-peak. IT could provide a better quality product and services for customers, but in itself may not reduce emissions if say peak load is switched to base load and the utility uses gas for peaking plants and coal for base-load plants. It could, however, enable the greater integration of more low-carbon-emitting technologies into the grid. The intermittent nature of many forms of renewable energy may require some form of energy storage or the use of a mix of energy sources and load responses to provide system reliability. To optimize the integration of intermittent renewable energy systems, IT could be used to determine generator preference and priority through a predetermined merit order based on both availability and market price. 4.3.9
Recovered energy
Assessing future costs and potentials across the range of energy-supply options is challenging. It is linked to the uncertainties of political support initiatives, technological development, future energy and carbon prices, the level of private and public investment, the rate of technology transfer and public acceptance, experience learning and capacity building and future levels of subsidies and support mechanisms. Just one such example of the complexity of determining the cost, potential and period before commercial delivery of a technology is the hydrogen economy. It encompasses all these uncertainties leading to considerable debate on its future technical and economic potential, and indeed whether a hydrogen economy will ever become feasible at all, and if so, when (USCCTP, 2005; IEA, 2003b). Bioenergy also exemplifies the difficulties when analysing current costs and potentials for a technology as it is based on a broad range of energy sources, geographic locations, technologies, markets and biomass-production systems. In addition, future projections are largely dependent upon RD&D success and economies of plant scale. Bioethanol from lignocellulose, for example, has been researched for over three decades with little commercial success to date. So there can be little certainty over the timing of future successes despite the recent advances of several novel biotechnology applications. Energy technological learning is nevertheless an established fact (WEC, 2001; Johansson, 2004; Section 2.7) and gives some confidence in projections for future market penetration. 4.4.1.
Carbon dioxide emissions from energy supply by 2030
A few selected baseline (IEA 2006b, WEO Reference; SRES A1; SRES B2 (Table 4.1); ABARE Reference) and policy mitigation scenarios (IEA 2006b, WEO Alternative policy; ABARE Global Technology and ABARE Global Technology +CCS) out to 2030 illustrate the wide range of possible future energy-sector mixes (Figure 4.25). They give widely differing views of future energy-supply systems, the primary-energy mix and the related GHG emissions. Higher energy prices (as experienced in 2005/06), projections that they will remain high (Section 4.3.1) or current assessments of CCS deployment rates (Section 4.3.6) are not always included in the scenarios. Hence, more recent studies (for example IEA 2006b, IEA 2006d; Fisher, 2006) are perhaps more useful for evaluating future energy supply potentials, though they still vary markedly.
Surplus heat generated during the manufacturing process by some industries such as fertilizer manufacturing, can be used 289
Energy Supply
Chapter 4
The ABARE global model, based on an original version produced for the Asia Pacific Partnership (US, Australia, Japan, China, India, Korea) (Fisher, 2006), is useful for mitigation analysis as it accounts for both higher energy prices and CCS opportunities. However, it does not separate ‘modern biomass’ from ‘other renewables’, and the modellers had also assumed that CCS would play a more significant mitigation role after 2050, rather than by the 2030 timeframe discussed here. The reference case (‘Ref’ in Figure 4.25) is a projection of key economic, energy and technology variables assuming the continuation of current or already announced future government policies and no significant shifts in climate policy. The Global Technology scenario (ABARE ‘Tech’) assumed that development and transfer of advanced energy-efficient technologies will occur at an accelerated rate compared with the reference case. Collaborative action from 2006 was assumed to affect technology development and transfer between several leading developed countries and hence lead to more rapid uptake of advanced technologies in electricity, transport and key industry sectors. The ‘Tech+CCS’ scenario assumed similar technology developments and transfer rates for electricity, transport and key industry sectors, but in addition CCS was utilized in all new coal- and gas-fired electricity generation plant from 2015 in US, Australia and Annex I countries and from 2020 in China, India and Korea. (EJ/yr)
(52.6)
900
800
values in brackets in Gt CO2-eq (37.5) 40.4
700
600 500
(58.3)
biomass (49.5) (34.1) (51.7)
other renewables
(26.1) hydro
400
nuclear gas
300 200
oil
100 coal 0 2004
IEA WEO reference
IEA 2030 SRES SRES ABARE B2 A1 Ref. Tech.Tech WEO +CCS. Altern. Biomass combined with other renewables
Figure 4.25: Indicative comparison of selected primary energy-supply baseline (reference) and policy scenarios from 2004 to 2030 and related total energy-related emissions in 2004 and 2030 (GtCO2-eq) Note: The IEA (2006b) Beyond Alternative Policy scenario (not shown) depicts that energy-related emissions could be reduced to 2004 levels. Source: Based on IEA, 2006b; IPCC, 2001; Price and de la Rue du Can, 2006; Fisher, 2006.
290
Table 4.6: Estimated carbon dioxide emissions from fossil-fuel use in the energy sector for 2002 and 2030 (MtCO2 /yr). 2002
2030
Transport (includes marine bunkers)
5999
10631
Industry, of which:
9013
13400
Electricity Heat:
- coal - oil - gas
Buildings, of which: Electricity Heat:
- coal - oil - gas
Total
4088
6667
2086 1436 1403
2413 2098 2222
8967
14994
5012
9607
495 1841 1618
356 2693 2338
23979a
39025
a
WEO, 2006 (IEA 2006b, unavailable at the time of the analysis) gives total CO2 emissions as 26,079 MtCO2 for 2004 Source: Price and de la Rue du Can, 2006.
4.4.2
Cost analyses
This section places emphasis on the costs and mitigation potentials of the electricity-supply sector. Heat and CHP potentials are more difficult to determine due to lack of available data, and transport potentials are analysed in Chapter 5. Cost estimates are sensitive to assumptions used and inherent data inconsistencies. They vary over time and with location and chosen technology. There is a tendency for some countries, particularly where regulations are lax, to select the cheapest technology option (at times using second-hand plant) regardless of total emission or environmental impact (Royal Academy of Engineering, 2004; Sims et al, 2003a). Here, based upon full life-cycle analyses in the literature, only broad cost comparisons are possible due to the wide variations in specific site costs and variations in labour charges, currency exchange rates, discount rates used, and plant capacity factors. Cost uncertainties in the electricity sector also exist due to the rate of market liberalization and the debate over the maximum level of intermittent renewable energy sources acceptable to the grid without leading to reliability issues and needing costly backup. One analysis compared the levelized investment, operations and maintenance (O&M), fuel and total generation costs from 27 coal-fired, 23 gas-fired, 13 nuclear, 19 wind- and 8 hydropower plants, either operational or planned in several countries (IEA/NEA, 2005). The technologies and plant types included several units under construction or due to be commissioned before 2015, but for which cost estimates had been developed through paper studies or project bids (Figure 4.27). The economic competitiveness of selected electricity-generation systems depends upon plant-specific features. The projected total levelized generation cost ranges tend to overlap (Figure
Chapter 4
Energy Supply
Figure 4.26: Predicted world energy sources to meet growing demand by 2030 based on updated SRES B2 scenario. Note: Related CO2 emissions from coal, gas and oil are also shown, as well as resources in 2004 (see Figure 4.4) and their depletion between 2004 and 2030 (vertical bars to the left). The resource efficiency ratio by which fast-neutron technology increases the power-generation capability per tonne of natural uranium varies greatly from the OECD assessment of 30:1 (OECD, 2006b). In this diagram the ratio used is up to 240:1 (OECD, 2006c). Source: IPCC, 2001; IIASA 1998
4.27) showing that under favourable circumstances, and given possible future carbon charge additions, all technologies can be economically justified as a component in a diversified energy technology portfolio. Construction cost assumptions ranged between 1000 and 1500 US$/kWe for coal plants; 400 and 800 US$/kW for CCGT; 1000 and 2000 US$/kW for wind; 1000 and 2000 US$/kW for nuclear and 1400 and 7000 US$/kW for hydro. Capacity factors of 85% were adopted for coal, gas and nuclear as baseload; 50% for hydro; 17 to 38% for onshore wind-power plants, and 40 to 45% for offshore wind. The costs of nuclear waste management and disposal, refurbishing and decommissioning were accounted for in all the studies reviewed, but remain uncertain. For example, decommissioning costs of a German pressurized water reactor were 155 €/kW, being 10% of the capital investment costs (IEA/ NEA, 2005). A further study, however, calculated life-cycle costs
of nuclear power to be far higher at between 47 and 70 US$/MWh by 2030 (MIT, 2003). Another cost comparison between coal, gas and nuclear options based upon five studies (WNA, 2005b) showed that nuclear was up to 40% more costly than coal or gas in two studies, but cheaper in the other three. Such projected costs depend on country- and project-specific conditions and variations in assumptions made, such as the economic lifetime of the plants and capacity factors. For example, nuclear and renewable energy plants could become more competitive if gas and coal prices rise and if the externality costs associated with CO2 emissions are included. In this regard, a European study (EU, 2005) evaluated external costs for a number of power-generation options (Figure 4.28) emphasizing the zero- or low-carbon-emitting benefits of nuclear and renewables and reinforcing the benefits 291
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250
Chapter 4
USD / MWh Investments 5%
Operation & Maintenance
10%
5%
Fuel cycle 5%
10%
Total costs
10%
5%
10%
200
150
100
50
0 C
G
N W
H
C
G
N W
H
C
G
N W
H
C
G
N W
H
C
G
N
C
G
N
C
G
N W
H
C
G
N W
H
Figure 4.27: Projected power-generating levelized costs for actual and planned coal (C), gas (G) nuclear (N), wind (W) and hydro (H) power plants with assumed capital interest rates of 5 or 10%. Notes: Bars depict 10 and 90 percentiles and lines extend to show minimum and maximum estimates. Other analyses provide different cost ranges (Table 4.7), exemplifying the uncertainties resulting from the discount rates and other underlying assumptions used. Source: IEA/NEA, 2005.
of CHP systems (Section 4.3.5) (even though only less efficient, small-scale CHP plants were included in the analysis). This comparison highlights the value from conducting full life-cycle
analyses when comparing energy-supply systems and costs (Section 4.5.3).
coal
oil
gas
hydro
eurocent/kWh
6
nuclear
photovoltaic
cogeneration (all exergy)
wind
gas
diesel
5
4
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1
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Figure 4.28: External costs (€/MWh) of current and more advanced electricity systems associated with emissions from the operation of the power plant and the rest of the fuel-supply chain (EU, 2005). ‘Rest’ is the external cost related to the fuel cycle (1 € = 1.3 US$ approximately). 292
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Table 4.7: The technical potential energy resource and fluxes available, potential associated carbon and projected costs (US$ 2006) in 2030 for a range of energy resources and carriers.
Technical potential EJa
Approximate inherent carbon (GtC)
Present energy costsc US$ (2005)
Oil
10,000-35,000e
200-1300
Natural gas
18,000-60,000
Energy resources and carriers
Coal Nuclear power Hydro > 10MW Solar PV Solar CSP Wind Geothermal
Projected costs in 2030 Investment US$/Wed
Generation US$/MWh
~9/GJ ~50/bbl ~48/MWh
n/a
50-100
170-860
~5-7/GJ ~37/MWh
0.2-0.8
40-60 +CCS 60-90
EIA/DOE, 2006 IPCC, 2005
130,000
3500
~3-4.5/GJ ~20/MWh
0.4-1.4
40-55 +CCS 60-85
EIA/DOE, 2006 IPCC, 2005
7400 (220,000)f
*b
10-120
1.5-3.0
25-75
1250
*
20-100/MWh
1.0-3.0
30-70
40,000
*
250-1600/MWh
0.6-1.2
60-250
50
*
120-450/MWh
2.0-4.0
50-180
15,000
*
40-90 MWh
0.4-1.2
30-80
50
*
40-100/MWh
1.0-2.0
30-80
large
*
80-400/MWh
?
70-200
Modern 9
6000
30-120/MWh
0.4-1.2
30-100
Biofuels
1.2
*
8-30/GJ
?
23-75 c/l
Hydrogen carrier
0.1
?
50/GJ
?
?
Ocean Biomass heat and power
Additional references Wall Street Journal, daily commodity prices
IAEA, 2006 Figures 4.27, 4.28
8-12/GJ Chapter 5, Figure 5.9 US NAE, 2004
Notes: a From Table 4.2. Generalized potential for extractable energy: for fossil fuels the remaining extractable resources; for renewable energy likely cumulative by 2030 b * = small amount c Prices volatile. Include old and new plants operating in 2006. Electricity costs for conversion efficiencies of 35% for fossil, nuclear and biomass d Excluding carbon dioxide capture and storage e Includes probable and unconventional oil and gas reserves f At 130 US$/kg and assuming all remaining uranium, either used in once-through thermal reactors or recycled through light-water reactors and in fast reactors utilizing depleted uranium and the plutonium produced (in parentheses) Source: Data from IEA, 2005a; IEA, 2006b; Johansson et al., 2004; IEA, 2004a; Fisher, 2006; IIASA/WEC, 1998; MIT, 2003.
A summary of cost-estimate ranges for the specific technologies as discussed in Section 4.3 is presented in Table 4.7. Costs and technical potentials out to 2030 show that abundant supplies of primary-energy resources will remain available. Despite uncertainty due to the wide range of assumptions, renewable energy fluxes and uranium resources are in sufficient supply to meet global primary-energy demands well past 2030 (Table 4.7). Proven and probable fossil-fuel reserves are also large, but concern over environmental impacts from combusting them could drive a transition to non-carbon energy sources. The speed of such a transition occurring depends, inter alia, on a number of things: how quickly investment costs can be driven down; confirmation that future life-cycle cost assessments for nuclear power, CCS and renewables are realistic; true valuation of external costs and their inclusion in energy prices; and what policies are established to improve energy security and reduce GHG emissions (University of Chicago, 2004).
4.4.3
Evaluation of costs and potentials for lowcarbon, energy-supply technologies
As there are several interactions between the mitigation options that have been described in Section 4.3, the following sections assess the aggregated mitigation potential of the energy sector in three steps based on the literature and using the World Energy Outlook 2004 ‘Reference’ scenario as the baseline (IEA, 2004a): • The mitigation potentials in excess of the baseline are quantified for a number of technologies individually (Sections 4.4.3.1–4.4.3.6). • A mix of technologies to meet the projected electricity demand by 2030 is compiled for OECD, EIT and non-OECD/ EIT country regions (Section 4.4.4) assuming competition between technologies, improved efficiency of conversion over time and that real-world constraints exist when building new (additional and replacement) plants and infrastructure. • The interaction of the energy supply sector with end-use power demands from the building and industry sectors is 293
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Table 4.8: Baseline data from the World Energy Outlook 2004 Reference scenario.
OECD EIT
Primary-energy fuel consumed for heat and electricity production in 2030 (EJ/yr)
Primary-energy fuel consumed for electricity in 2030a (EJ /yr)
Final electricity demand in 2030 (TWh/yr)
Increase in new power demand 2002 to 2030 (TWh)
Total emissions from electricity in 2030 (GtCO2-eq/yr)
118.6
115.4
14,244
4,488
5.98
29.3
22.1
2,468
983
1.17
Non-OECD
128.5
125.3
14,944
10,111
8.62
World
276.4
262.8
31,656
15,582
15.77
a
Final electricity generation was based on the electrical efficiencies calculated from 2002 data (IEA, 2004a Appendix 1) including a correction for the share of final heat in the total final energy consumption (see Chapter 11). Source: IEA, 2004a.
then analysed (Section 11.3). Any savings of electricity and heat resulting from the uptake of energy-efficiency measures will result in some reduction in total demand for energy, and hence lower the mitigation potential of the energy supply sector. Mitigation in the electricity supply sector can be achieved by optimization of generation plant-conversion efficiencies, fossilfuel switching, substitution by nuclear power (Section 4.3.2) and/or renewable energy (4.3.3) and by CCS (4.3.6). These low-carbon energy technologies and systems are unlikely to be widely deployed unless they become cheaper than traditional generation or if policies to support their uptake (such as carbon pricing or government subsidies and incentives) are adopted. The costs (Table 4.7) and mitigation potentials for the major energy-supply technologies are compared and quantified out to 2030 based on assumptions taken from the literature, particularly the recent IEA Energy Technology Perspectives (ETP) report (IEA, 2006a). The assessment of the electricity-supply sector potentials are partly based on the TAR assessment2 but use more recent data and revised assumptions. Heat and CHP potentials (Section 4.3.5) were difficult to assess as reliable data are unavailable. For this reason the IEA aggregates commercial heat with power (IEA, 2004a, 2005a, 2006b). An estimate of the potential mitigation from increased CHP uptake by industry by 2050 was 0.2–0.4 GtCO2 (IEA, 2006a), but is uncertain so heat is not included here. The 2030 electricity sector baseline (Table 4.8; IEA, 2004a) was chosen because the SRES B2 scenario (Figure 4.26) provided insufficient detail and the latest WEO (IEA, 2006b) had not been published at the time. Estimates of the 2030 global demand for power are disaggregated for OECD, EIT, and nonOECD/EIT regions. The WEO 2004 baseline assumed that the 44% of coal in the power-generation primary fuel mix in 2002 would change to 42% by 2030; oil from 8% to 4%; gas 21% to
2
29%; nuclear 18% to 12%; hydro would remain the same at 6% (using the direct equivalent method); biomass 2% to 4%, and other renewables 1% to 3%. This analysis quantifies the mitigation potential at the high end of the range for each technology by 2030 above the baseline. It assumes each technology will be implemented as much as economically and technically possible, but is limited by the practical constraints of stock turnover, rate of increase of manufacturing capacity, training of specialist expertise, etc. The assumptions used are compared with other analyses reported in the literature. Since, in reality, each technology will be constrained by what will be happening elsewhere in the energysupply sector, they could never reach this total ‘maximum’ potential collectively, so these individual potentials cannot be directly added together to obtain a projected ‘real’ potential. Further analysis based on a possible future mix of generation technologies is therefore provided in Section 4.4.4 and further in Chapter 11, accounting for energy savings reducing the total demand. Emission factors per GJ primary fuel for CO2, N2O and CH4 (IPCC, 1997) were used in the analysis but the nonCO2 gases accounted for less than 1% of emissions. 4.4.3.1
Plant efficiency and fuel switching
Reductions in CO2 emissions can be gained by improving the efficiency of existing power generation plants by employing more advanced technologies using the same amount of fuel. For example, a 27% reduction in emissions (gCO2/kWh) is possible by replacing a 35% efficient coal-fired steam turbine with a 48% efficient plant using advanced steam, pulverized-coal technology (Table 4.9). Replacing a natural gas single-cycle turbine with a combined cycle (CCGT) of similar output capacity would help reduce CO2 emissions per unit of output by around 36%. Switching from coal to gas increases the efficiency of the power plant because of higher operating temperatures, and
The TAR (IPCC, 2001) estimated potential emission reductions of 1.3–2.5 GtCO2 (0.35–0.7 GtC) by 2020 for less than 27 US$/tCO2 (100 US$/tC) based on fuel switching from coal to gas; deployment of nuclear, hydro, geothermal, wind, biomass and solar thermal; the early uptake of CCS; and co-firing of biomass with coal.
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Table 4.9: Reduction in CO2 emission coefficient by fuel substitution and energy conversion efficiency in electricity generation.
Existing generation technology
Emission reduction per unit of output
Mitigation substitution option
Efficiency (%)
Emission coefficient (gCO2/kWh)
Coal, steam turbine
35
973
Coal, steam turbine
35
Fuel oil, steam turbine
Efficiency (%)
Emission coefficient (gCO2/kWh)
(gCO2/kWh)
Pulverised coal, advanced steam
48
710
-263
973
Natural gas, combined cycle
50
404
-569
35
796
Natural gas, combined cycle
50
404
-392
Diesel oil, generator set
33
808
Natural gas, combined cycle
50
404
-404
Natural gas, single cycle
32
631
Natural gas, combined cycle
50
404
-227
Energy source
Switching option
Source: Danish Energy Authority, 2005.
when used together with the more efficient combined-cycle results in even higher efficiencies (IEA, 2006a). Emission savings (gCO2-eq/kWh) were calculated before and after each substitution option (based on IPCC 1996 emission factors). The baseline scenario (IEA, 2004a) assumed a 5% CO2 reduction from fossil-fuel mix changes (coal to gas, oil to gas etc.) and a further 7% reduction in the Alternative Policy scenario from fuel switching in end uses (see Chapters 6 and 7). By 2030, natural gas CCGT plants displacing coal, new advanced steam coal plants displacing less-efficient designs, and the introduction of new coal IGCC plants to replace traditional steam plants could provide a potential between 0.5 and 1.4 GtCO2 depending on the timing and sequence of economics and policy measures (IEA, 2006a). IEA analysis also showed that up to 50 GW of stationary gas-fired fuel cells could be operating by 2030, growing to around 3% of all power generation capacity by 2050 and giving about 0.5 Gt CO2 emissions reduction (IEA, 2006j). This potential is uncertain, however, as it relies on appropriate fuel-cell development and is not included here. By 2030, a proportion of old heat and power plants will have been replaced with more modern plants having higher energy efficiencies. New plants will also have been built to meet the growing world demand. It is assumed that after 2010
only the most efficient plant designs available will be built, though this is unlikely and will therefore increase future CO2 emissions above the potential reductions. The coal that could be displaced by gas and the additional gas power generation required is assessed by region (Table 4.10). A plant life time of 50 years; a 2%-per-year replacement rate in all regions starting in 2010; 20% of existing coal plants replaced by 2030 and 50% of all new-build thermal plants fuelled by gas, are among the most relevant assumptions. The cost of fuel switching partly depends on the difference between coal and gas prices. For example if mitigation costs below 20 US$/tCO2-eq avoided, this would imply a relatively small price gap between coal and gas, although since fuel switching to a significant degree would affect natural gas prices, actual future costs are difficult to estimate with accuracy. Generation costs are assumed to be 40–55 US$/MWh for coal-fired and 40–60 US$/MWh for gasfired power plants.
4.4.3.2
Nuclear
Proposed and existing fossil fuel power plants could be partly replaced by nuclear power plants to provide electricity
Table 4.10: Potential GHG emission reductions by 2030 from coal-to-gas fuel switching and improved efficiency of existing plant.
OECD EIT
Cost ranges (US$/tCO2-eq)
Coal displaced by gas and improved efficiency (EJ/yr)
Additional gas power required (TWh/yr)
Emissions avoided (GtCO2-eq/yr)
Lowest
Highest
7.18
947
0.39
0
12
0.73
79
0.04
0
10
Non-OECD
10.92
1392
0.64
0
11
World
18.83
2418
1.07
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Chapter 4
Table 4.11: Potential GHG emission reduction and cost ranges in 2030 from nuclear-fission displacing fossil-fuel power plants. Cost ranges (US$/tCO2-eq)
Potential contribution to electricity mix (%)
Additional generation above baseline (TWh/yr)
Lowest
Highest
OECD
25
1424
0.93
-24
25
EIT
25
345
0.23
-23
22
Non-OECD
10
974
0.72
-21
21
World
18
2743
1.88
Emissions avoided (GtCO2-eq/yr)
Table 4.12: Potential GHG emission reduction and cost ranges in 2030 as a result of hydro power displacing fossil-fuel thermal power plants. Additional generation above baseline (TWh/yr)
Net emissions avoided (GtCO2-eq/yr)
Lowest
Highest
OECD
15
608
0.39
-16
3
EIT
15
0
0
0
-14
41
0.0
Non-OECD
20
643
0.48
World
17
1251
0.87
and heat. Since the nuclear plant and fuel system consumes only small quantities of fossil fuels in the fuel cycle, net CO2 emissions could be lowered significantly. Assessments of future potential for nuclear power are uncertain and controversial. The 2006 WEO Alternative scenario (IEA, 2006b) anticipated a 50% increase in nuclear energy (to 4106 TWh/yr) by 2030. The ETP report (IEA, 2006a) assumed a mitigation potential of 0.4–1.3 GtCO2 by 2030 from the construction of Generation II, III, III+ and IV nuclear plants (Section 4.3.2). From a review of the literature and the various scenario projections described above (for example Figure 4.25), it is assumed that by 2030 18% of total global power-generation capacity could come from existing nuclear power plants as well as new plants displacing proposed new coal, gas and oil plants in proportion to their current share of the baseline (Table 4.11). The rate of build required is possible (given the nuclear industry’s track record for building reactors in the 1970s) and generating costs of 25–75 US$/MWh are assumed (Section 4.4.2). However, there is still some controversy regarding the relatively low costs shown by comparative life-cycle analysis assessments reported in the literature (Section 4.4.2) and used here. 4.4.3.3 Renewable energy Fossil fuels can be partly replaced by renewable energy sources to provide heat (from biomass, geothermal or solar) or electricity (from wind, solar, hydro, geothermal and bioenergy generation) or by CHP plants. Ocean energy is immature and assumed unlikely to make a significant contribution to overall power needs by 2030. Net GHG emissions avoided are used in
3
Cost ranges (US$/tCO2-eq)
Potential contribution to electricity mix (%)
the analysis since most renewable energy systems emit small amounts of GHG from the fossil fuels used for manufacturing, transport, installation and from any cement or steel used in their construction. Overall, net GHG emissions are generally low for renewable energy systems (Figure 4.19) with the possible exception of some biofuels for transport, where fossil fuels are used to grow the crop and process the biofuel. Hydro The ETP (IEA, 2006a) stated the technical potential of hydropower to be 14,000 TWh/yr, of which around 6000 TWh/yr (56 EJ) could be realistic to develop (IHA, 2006). The WEO Alternative scenario (IEA, 2006b) assumed an increased share for hydro generation above baseline, reaching 4903 TWh/yr by 20303. IEA (2006a) suggested hydropower (both small and large) could offset fossil-fuel power plants to give a mitigation potential between 0.3–1.0 GtCO2/yr by 2030. Here it is assumed that enough existing and new sites will be available to contribute around 5500 TWh/yr (17% of total electricity generation) by 2030 as a result of displacing coal, gas and oil plants based on their current share of the base load (Table 4.12). Future costs range from 30–70 US$/MWh for good sites with high hydrostatic heads, close proximity to load demand, and with good all-year-round flow rates. Smaller plants and those installed in less-favourable terrain at a distance from load could cost more. GHG emissions from construction of hydro dams and possible release of methane from resulting reservoirs (Section 4.3.3.1) are uncertain and not included here.
Although nuclear (Table 4.11) and hydro both offer a similar contribution to the global electricity mix today and by 2030, their emission reduction potentials differ due to variations in assumptions of regional shares and baseline. Estimates in the baseline were 4248 TWh yr-1 from hydro by 2030 compared with 2929 TWh yr-1 from nuclear (IEA, 2004a).
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Table 4.13: Potential GHG emission reduction and costs in 2030 from wind power displacing fossil-fuel thermal power plants. Potential contribution to electricity mix (%) OECD EIT
Additional generation above baseline (TWh/yr)
Net extra emissions reductions (GtCO2-eq/yr)
Cost ranges (US$/tCO2-eq) Lowest
Highest
10
687
0.45
-16
33
5
99
0.06
-16
30
-14
27
Non-OECD
5
572
0.42
World
7
1358
0.93
Table 4.14: Potential emissions reduction and cost ranges in 2030 from bioenergy displacing fossil-fuel thermal power plants. Potential contribution to electricity mix (%)
Additional generation above baseline (TWh/yr)
Net emissions reductions (GtCO2-eq/yr)
Cost ranges (US$/tCO2-eq) Lowest
Highest
OECD
5
307
0.20
-16
63
EIT
5
112
0.07
-16
60
-14
54
Non-OECD World
10
1283
0.95
7
1702
1.22
Wind The 2006 WEO Reference scenario baseline (IEA, 2006b) assumed 1132 TWh/yr (3.3% of total global electricity) of wind generation in 2030 rising to a 4.8% share in the Alternative Policy scenario. However, wind industry ‘advanced’ scenarios are more optimistic, forecasting up to a 29.1% share for wind by 2030 with a mitigation potential of 3.1 GtCO2/yr (GWEC, 2006). The ETP mitigation potential assessment (IEA, 2006a) for on- and offshore wind power by 2030 ranged between 0.3 and 1.0 GtCO2/yr. In this analysis on- and offshore wind power is assumed to reach a 7% share by 2030, mainly in OECD countries, and to displace new and existing fossil-fuel power plants according to the relevant shares of coal, oil and gas in the baseline for each region (Table 4.13). Intermittency issues on most grids would not be limiting at these low levels given suitable control and back-up systems in place. The costs are very site specific and range from 30 US$/MWh on good sites to 80 US$/MWh on poorer sites that would also need to be developed if this 7% share of the total mix is to be met. Bioenergy (excluding biofuels for transport) Large global resources of biomass could exist by 2030 (Chapters 8, 9 and 10), but confidence in estimating the bioenergy heat and power potential is low since there will be competition for these feedstocks for biomaterials, chemicals and biofuels. Bioenergy in its various forms (landfill gas, combined heat and power, biogas, direct combustion for heat etc.) presently contributes 2.6% to the OECD power mix, 0.4% to EIT and 1.5% to non-OECD. The WEO 2006 (IEA, 2006b) assumed 805 TWh of biomass power generation in 2030 rising 22% to 983 TWh under the Alternative scenario to then give 3% of total electricity generation. The ETP gave a bioenergy potential ranging between 0.1 and 0.3 GtCO2 /yr by 2030. The
baseline (IEA, 2004a) assumed biomass and waste for heat and power generation will rise from 2% of primary fuel use (3.2 EJ) in 2002 to 4% (10.8 EJ) by 2030. Heat and CHP estimates are wide ranging so cannot be included in this analysis, even though the bioenergy potential could be significant. However, any heat previously utilized from displaced coal and gas CHP plants could easily be supplied from biomass, with more biomass available for use in stand-alone heat plants (Chapter 11). In this analysis, a 5% share in OECD regions is assumed feasible, relying on co-firing in existing and new coal plants and with 7–8% of the total replacement capacity built being bioenergy plants. In EIT regions, the available forest biomass could be utilized to gain 5% share and in non-OECD regions, where there are less stock turnover issues than in the OECD, 10% of power could come from new bioenergy plants (Table 4.14). A total potential by 2030 of 5% is assumed based on costs of 30–100 US$/MWh. The biomass feedstock required to meet these potentials, assuming thermalconversion efficiencies of 20–30%, would be around 9–13 EJ in OECD, 1–3 EJ in EIT, and 18–27 EJ in non-OECD regions. Little additional bioenergy capacity above that already assumed in the baseline is anticipated in EIT regions where only a small contribution is expected compared with developing countries. Small inputs of fossil fuels are often used to produce, transport and convert the biomass (IEA, 2006h), but the same is true when using the fossil fuels it replaces. Since both are of a similar order of magnitude, and these emissions are already accounted for in the overall total for fossil fuels, bioenergy is credited with zero emissions (in compliance with IPCC guidelines).
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Table 4.15: Potential emissions reduction and cost ranges in 2030 from geothermal displacing fossil-fuel thermal power plants. Potential contribution in electricity mix (%)
Additional geothermal (TWh/yr)
Net emissions avoided (GtCO2-eq/yr)
Cost ranges (US$/tCO2-eq) Lowest
Highest
137
0.09
-16
33
2
44
0.03
-16
30
3
413
0.31
-14
27
2
594
0.43
OECD
2
EIT Non-OECD World
Table 4.16: Potential emission reduction and cost ranges in 2030 from solar PV and CSP displacing fossil-fuel thermal power plants. Potential contribution to electricity mix (%) OECD
1
EIT Non-OECD World
Additional generation above baseline (TWh/yr)
Cost ranges (US$/tCO2-eq) Lowest
Highest
44
0.03
61
294
1
21
0.01
60
288
2
275
0.21
53
257
2
340
0.25
Geothermal The installed geothermal-generation capacity of over 8.9 GWe in 24 countries produced 56.8 TWh (0.3%) of global electricity in 2004 and is growing at around 20%/yr (Bertani, 2005) with the baseline giving 0.05% of total generation by 2030. IEA WEO 2006 (IEA, 2006b) assumed 174 TWh/yr by 2030 rising 6% to 185 TWh under the Alternative scenario. The ETP (IEA, 2006a) gave a potential of 0.1–0.3 GtCO2-eq/yr by 2030. In this analysis, generation costs of 30–80 US$/MWh are assumed to provide a 2% share of the total 2030 energy mix. Direct heat applications are not included. Although CO2 emissions are assumed to be zero, as for other renewables, this may not always be the case depending on underground CO2 released during the heat extraction. Solar Concentrating solar power (CSP) and photovoltaics (PV) can theoretically gain a maximum 1–2% share of the global electricity mix by 2030 even at high costs. The 2006 WEO Reference scenario (IEA, 2006b) estimated 142 TWh/yr of PV generation in 2030 rising to 237 TWh in the Alternative scenario but still at <1% of total generation. EPRI (2003) assessed total PV capacity to be 205 GW by 2020 generating 282 TWh/yr or about 1% of global electricity demand. Other analyses range from over 20% of global electricity generation by 2040 (JägerWaldau, 2003) to 0.008% by 2030 with mitigation potential for both PV and CSP likely to be <0.1 GtCO2 in 2030 (IEA, 2006a) The calculated minimum costs for even the best sites resulted in relatively high costs per tonne CO2 avoided (Table 4.16). The baseline (IEA, 2004a) gave the total solar potential as 466 TWh or 1.4% of total generation in 2030.
298
Emissions reductions (GtCO2-eq/yr)
In this analysis, generating costs from CSP plants could fall sufficiently to compete at around 50–180 US$/MWh by 2030 (Trieb, 2005; IEA, 2006a). PV installed costs could decline to around 60–250 US$/MWh, the wide range being due to the various technologies being installed on buildings at numerous sites, some with lower solar irradiation levels. Penetration into OECD and EIT markets is assumed to remain small with more support for developing country electrification. 4.4.3.4
Carbon dioxide capture and storage
In the absence of explicit policies, CCS is unlikely to be deployed on a large scale by 2030 (IPCC, 2005). The total CO2 storage potential for each region (Hendriks et al. 2004; Table 4.17) appears to be sufficient for storage over the next few decades, although capacity assessments are still under debate (IPCC, 2005). The proximity of a CCS plant to a storage site affects the cost, but this level of analysis was not considered here. CCS does not appear in the baseline (IEA, 2004a). Penetration by 2030 is uncertain as it depends both on the carbon price and the rate of technological advances in costs and performance. Coal CCS ABARE (Fisher, 2006) suggested that worldwide by 2030, 1811 TWh/yr would be generated from coal with CCS (17 EJ); 7871 TWh (73 EJ) from coal without; 1492 TWh (14 EJ) from gas with; and 6315 TWh (59 EJ) from gas without. CCS would thus result in around 4.4 GtCO2 of GHG emissions avoided in 2030 giving a 17% reduction from the reference base case level (Figure 4.25). In contrast, the ETP mitigation assessments for CCS with coal plants ranged between only 0.3 and 1.0 GtCO2 in 2030 (IEA, 2006a), given that commercial-scale CCS demonstration will be needed before widespread deployment.
Chapter 4
Energy Supply
Table 4.17: Potential emissions reduction and cost ranges in 2030 from CCS used with coal-fired power plants. Share of plants with CCS (%)
Coal-fired power generation with CCS
OECD
9
388
EIT
4
Non-OECD
4
World
6
655
a Hendriks
Annual emissions avoided (GtCO2-eq/yr)
Cost ranges (US$/tCO2-eq)
Total potential storage volumea (GtCO2)
Lowest
Highest
0.28
71-1025
28
42
14
0.01
114-1250
22
33
253
0.20
291-3600
26
39
0.49
476-5875
et al, 2004
Table 4.18: Potential emissions reduction and cost ranges in 2030 from CCS used with gas-fired power plants.
Share of plants with CCS (%) OECD
7
EIT Non-OECD World
Gas-fired power generation with CCS (TWh/yr)
Annual emission avoided (GtCO2-eq/yr)
Cost ranges (US$/tCO2-eq)
Total capture from both coal + gas, 2015-2030 (GtCO2)
Lowest
Highest
8.37
52
79
243
0.09
5
78
0.04
2.03
43
64
5
276
0.09
12.56
51
76
6
597
0.22
22.96
In this analysis, CCS is assumed to begin only after 2015 in OECD countries and after 2020 elsewhere, linked mainly with advanced steam coal plants installed with flue gas separation, although these IGCC plants and oxyfuel systems are only just entering the market (Dow Jones, 2006). Assuming a 50-year life of coal plants (IEA, 2006a) and that 30% of new coal plants built in OECD and 20% elsewhere will be equipped with CCS, then the replacement rate of old plants by new designs with CCS incorporated is 0.6% per year in OECD and 0.4% elsewhere. Then 9% of total new and existing coal-fired plants will have CCS by 2030 in the OECD region and 4% elsewhere. Assuming 90% of the CO2 can be captured and a reduced fuel-to-electricity conversion efficiency of 30% (leading to less power available for sale – IPCC, 2005), then the additional overall costs range between 20 and 30 US$/MWh depending on the ease of CO2 transport and storage specific to each plant (Table 4.17). Gas CCS The assumed life of a CCGT plant is 40 years, and with 20% of new gas-fired plants utilizing CCS starting in 2015 in OECD countries and 2020 elsewhere, then the replacement rate of old plants by new designs integrating CCS is 0.5% per year. By 2030 7% of all OECD gas plants will have CCS and 5% elsewhere. Assuming 90% of the CO2 is captured, a reduction of gas-fired power plant conversion efficiency of 15% (IPCC, 2005), and an additional overall cost ranging between 20 and 30 US$/MWh generated, then the costs and potentials by 2030 (compared with the IEA (2004a) baseline of no CCS) are assessed (Table 4.18). The costs for both coal and gas CCS compare well with the IPCC (2005) range of 15–75 US$/tCO2 (Table 4.5).
4.4.3.5
Summary
The cost ranges (US$/tCO2-eq avoided) for each of the technologies analysed in Section 4.4.3 are compared (Table 4.19). The percentage share of the total potential is shown spread across the defined cost class ranges for each region and technology. This assumes that a linear relationship exists between the lowest and highest costs as presented in Section 4.4.3 for each technology and region. Since each technology is assumed to be promoted individually and crowding-out by other technologies under real-world constraints is ignored, the potentials in Table 4.19 are independent and cannot be added together. 4.4.4
Electricity-supply sector mitigation potential and cost of GHG emission avoidance
To provide a more realistic indication of the total mitigation potential for the global electricity sector, further analysis is conducted based on the literature, and assuming that no additional energy-efficiency measures in the building and industry sectors will occur beyond those already in the baseline. (Section 11.3.1 accounts for the impacts of energy efficiency on the heat and power-supply sector). The WEO 2004 baseline (IEA, 2004a) is used, based on data from Price and de la Rue du Can, (2006). The fuel-to-electricity conversion efficiencies were derived from the correction of the heat share in the WEO 2004 data, by assuming the share of heat in the total primary energy supply was constant from 2002 onwards.
299
Energy Supply
Chapter 4
Table 4.19: Potential GHG emissions avoided by 2030 for selected, electricity generation mitigation technologies (in excess of the World Energy Outlook 2004 Reference baseline, IEA, 2004a) if developed in isolation and with the estimated mitigation potential shares spread across each cost range (2006 US$/tCO2-eq) for each region. Regional groupings Fuelswitch and plant efficiency
Nuclear
Hydro
Wind
Bioenergy
Geothermal
Solar PV and CSP
CCS + coal
CCS + gas
Mitigation potential; total emissions saved in 2030 (GtCO2-eq)
Mitigation potential (%) spread over cost ranges (US$/tCO2-eq avoided) 0-20
OECD
0.39
100
EIT
0.04
100
Non-OECD
0.64
100
20-50
World
1.07
OECD
0.93
50
50
EIT
0.23
50
50
Non-OECD
0.72
50
50
World
1.88
OECD
0.39
85
15
EIT
0.00 25
35
40
50-100
Non-OECD
0.48
World
0.87
OECD
0.45
35
40
25
EIT
0.06
35
45
20
Non-OECD
0.42
35
50
15
World
0.93
OECD
0.20
20
25
40
15
EIT
0.07
20
25
40
15
Non-OECD
0.95
20
30
45
5
World
1.22
>100
OECD
0.09
35
40
25
EIT
0.03
35
45
20
Non-OECD
0.31
35
50
15
World
0.43
OECD
0.03
20
80
EIT
0.01
20
80
Non-OECD
0.21
25
75
World
0.25
OECD
0.28
100
EIT
0.01
100
Non-OECD
0.20
100
World
0.49
OECD
0.09
EIT
0.04
Non-OECD
0.09
World
0.22
The baseline By 2010 total power demand is 20,185 TWh with 13,306 TWh generation coming from fossil fuels (65.9% share of the total generation mix), 3894 TWh from all renewables (19.3%), and 2985 TWh from nuclear (14.8%). Resulting emissions are 11.4 GtCO2-eq. By 2030 the increased electricity 300
<0
100 30
70 100
demand of 31,656 TWh is met by 22,602 TWh generated from fossil fuels, 6,126 TWh from renewables, and 2,929 TWh from nuclear power. The fossil-fuel primary energy consumed for electricity generation in 2030 produces 15.77 GtCO2-eq of emissions (IEA, 2004a; Table 4.8).
Chapter 4
New electricity generation plants to be built between 2010 and 2030 are to provide additional generating capacity to meet the projected increase in power demand, and to replace capacity of old, existing plants being retired during the same period. Additional capacity built after 2010, consumes an additional 82.5 EJ/yr of primary energy in order to generate 11,471 TWh/yr more electricity by 2030. Replacement capacity built during the period consumes 72 EJ/yr in 2030 and generates 8074 TWh/yr. Therefore, the total generation from new plants in the baseline is 19,545 TWh/yr by 2030, of which 14,618 TWh/yr comes from fossil-fuel plants (75%), 3787 TWh/yr from other renewables (19%), and 1140 TWh/yr from nuclear power (6%) (IEA, 2004a).
Sector analysis from 2010 to 2030 The potential for the global electricity sector to reduce baseline GHG emissions as a result of the greater uptake of lowand zero-carbon-emitting technologies is assessed. The method employed is outlined below. Fossil-fuel switching from coal to gas; substitution of coal, gas and oil plants with nuclear, hydro, bioenergy and other renewables (wind, geothermal, solar PV and solar CSP), and the uptake of CCS are all included. • For each major world country-grouping (OECD Pacific, US and Canada, OECD Europe, EIT, East Asia, South Asia, China, Latin America, Mexico, Middle East and Africa), WEO 2004 baseline data (Price and de la Rue du Can, 2006; IEA, 2004a) are used to show the capacity of fossil-fuel thermal electricity generation per year that could be substituted after 2010, assuming a linear replacement rate and a 50-year life for existing coal, gas and oil plants. The results are then aggregated into OECD, EIT and nonOECD/EIT regional groupings. • New generation plants built by 2030 to meet the increasing power demand are shared between fossil fuel, renewables, nuclear and, after 2015, coal and gas-fired plants with CCS. The shares of total power generation assumed for each of these technologies by 2030 are based on the literature (Section 4.4.3), but also depend partly on their relative costs (Table 4.19). The relatively high shares assumed for nuclear and renewable energy, particularly in OECD countries, are debatable, but supported to some extent by European Commission projections (EC, 2007). • No early retirements of plant or stranded assets are contemplated (although in reality a faster replacement rate of existing fossil-fuel capacity could be possible given more stringent policies in future to reduce GHG emissions). The assumed replacement rates of old fossil-fuel plant capacity by nuclear, and renewable electricity, and the uptake of CCS technologies, are each based on the regional power mix shares of coal, gas and oil plants operating in the baseline. • In reality, the future value of carbon will likely affect the actual generation shares for each technology, as will any mitigation policies in place before 2030 that encourage reductions of GHG emissions from specific components of the energy-supply sector.
Energy Supply
• It is assumed that after 2010 only power plants with higher conversion efficiencies (Table 4.20) are built. • As fuel switching from coal to natural gas supply is assessed to be an option with relatively low costs, this is implemented first with 20% of new proposed coal-fired power plants substituted by gas-fired technologies in all regions (based on Section 4.4.3.1). • It is assumed that, where cost-effective, some of the new fossil-fuel plants required according to the baseline (after adjustments for the previous step) are displaced by lowand zero-carbon-intensive technologies (wind, geothermal, hydro, bioenergy, solar, nuclear and CCS) in proportion to their relative costs and potential deployment rates. The resulting GHG emissions avoided are assessed. • It is assumed that by 2030, wind, solar CSP and solar PV plants that displace new and replacement fossil-fuel generation are partly constrained by related environmental impact issues, the relatively high costs for some renewable plants compared to coal, gas and nuclear, and intermittency issues in power grids. However, developments in energy-storage technologies, supportive policy trends and recognition of co-benefits are assumed to partly offset these constraints. Priority grid access for renewables is also assumed. Thus, reasonably high shares in the mix become feasible (Table 4.20). • The share of electricity generation from each technology assumes that the maximum resource available is not exceeded. The available energy resources are evaluated on a regional basis to ensure all assumptions can be met in principle. − Any volumes of biomass needed above those available from agricultural and forest residues (Chapters 8 and 9) will need to be purpose-grown, so could be constrained by land and water availability. While there is some uncertainty in this respect, there should be sufficient production possible in all regions to meet the generation from bioenergy as projected in this analysis. − Uranium fuel supplies for nuclear plants should meet the assumed growth in demand, especially given the anticipation of ‘Gen III’ plant designs with fuel recycling coming on stream before 2030. − There is sufficient storage capacity for sequestering the estimated capture of CO2 volumes in all regions given the anticipated rate of growth of CCS over the next few decades (Hendricks et al., 2004). • CCS projects for both coal- and gas-fired power plants are deployed only after 2015, assuming commercial developments are unavailable until then.
301
302 3729 166 2459 289 874 126 164
11471
20185
7807
7137
32 29 39 33 100 48 36
3232 646 1401 231 1472 85 70
722 13 -8 672 -20 35 7 23
1746 381 69 652 292 338 4 10
41 40 48 33 100 28 63
38 38 46 33 100 19 28
2942 657 -163c 1771 -325 127 168 707
(TWh)
11302 4079 472 2374 2462 1402 237 276
(TWh)
(%)
Generation from additional new plant by 2030
8074
1293 258 560 92 589 34 28
2855
698 152 28 261 117 135 2 4
4521 1632 189 950 985 561 95 110
(TWh)
Generation from new plant replacing old, existing 2010 plant by 2030
1697 179 2279 1356 2106 1294 1154 598 19545
0
123 10662
1282 1420 46 7 357 442 170 109 167
1345
1133 120 1856 1356 2106 1443 1303
222
29 4 240 442 170 121 191
2082
b
3.95
2.06
0.32
6.44
3.44
0.42
<50 US$/t 2.58
7.22
4.08
0.49
<100 US$/t 2.66
Total GtCO2-eq avoided by fuel switching, CCS and displacing some fossil fuel generation with low carbon option of wind, solar, geothermal, hydro, nuclear and biomass
<50 US$/t <100 US$/t TWh TWh <20 US$/t 7463 1.58 121 0 2 0 637 458 2084 1777 1295 1111 499 509 1544 1526
2807 297 3114 1356 1463 621 1004
0
72 11 537 442 170 47 142
0
899 13 1793 2084 1295 263 1116
<20 US$/t TWh
Share of mix of generation of total new and replacement plant built by 2030 including CCS at various costs of US$/tCO2-eq avoidedb
efficiencies calculated from WEO 2004 (IEA, 2004b) = Power output (EJ) / Estimated power input (EJ). See Appendix 1, Chapter 11. At higher costs of US$/tCO2 avoided, more coal, oil and gas power generation is displaced by low- and zero-carbon options. Since nuclear and hydro are cost competitive at <20 US$/tCO2-eq avoided in most regions (Table 4.9),and the rate of building new plants is constrained, their share remains constant. c Negative data depicts a decline in generation, which was included in the analysis. Source: Based on IEA, 2004a.
a Implied
OECD Coal Oil Gas Nuclear Hydro Biomass Other renewables CCS EIT Coal Oil Gas Nuclear Hydro Biomass Other renewables CCS Non-OECD/ EIT Coal Oil Gas Nuclear Hydro Biomass Other renewables CCS TOTAL
Existing mix of power generation in 2010
Power plant efficiencies by 2030 (based on IEA 2004a)a
Table 4.20: Projected power demand increase from 2010 to 2030 as met by new, more efficient additional and replacement plants that will displace 60% of existing plants at the end of their life. The potential mitigation above the baseline of GHG avoided for <20 US$/t, <50 US$/t and <100 US$/tCO2-eq results from fuel switching from coal to gas, a portion of fossil-fuel generation being displaced by nuclear, renewable energy and bioenergy in each region and CCS.
Energy Supply Chapter 4
Chapter 4
4.4.4.1
Energy Supply
Mitigation potentials of the electricity supply sector
Based on the method described above and the results from the analysis (Table 4.20), the following conclusions can be drawn. With reference to the baseline: a) power plants existing in 2010 that remain in operation by 2030 (Table 4.20), including coal, oil and gas-fired, continue to generate 12,111 TWh/yr in 2030 (38% of the total power demand) and produce 5.77 GtCO2-eq/yr of emissions; b) new additional plants to be built over the 20-year period from 2010 generate 11,471 TWh/yr by 2030 and new plants built to replace old plants generate 8074 TWh/yr; c) the share of all new build plants burning coal, oil and gas produce around 10 GtCO2-eq/yr by 2030, thereby giving total baseline emissions of 15.77 GtCO2-eq/yr (Table 4.8). For costs < 20 US$/tCO2-eq avoided: a) The baseline generation from fossil fuel-fired plants in 2030 of 22,602 TWh (including 14,618 TWh from new generation) reduces by 22.5% to 17,525 TWh (including 9541 TWh of new build generation) due to the increased uptake of lowand zero-carbon technologies. This is a reduction from the 71% of total generation in the baseline to 55%. b) Of this total, fuel switching from coal to gas results in additional gas-fired plants generating 1,495 TWh/yr by 2030, mainly in non-OECD/EIT countries, and thereby avoiding 0.67 GtCO2-eq/yr of emissions. c) Renewable energy generation increases from the 2030 baseline of 6126 TWh/yr to 7904 TWh/yr (6122 TWh/yr from new generation plus 2336 TWh/yr remaining in operation from 2010). The share of generation increases from 19.4% in 2010 to 26.7% by 2030. d) The nuclear power baseline of 2929 TWh/yr by 2030 (9.3% of total generation) increases to 5673 TWh/yr (17.9% of generation), of which 3882 TWh/yr is from newly built plants. e) Overall, GHG emissions are reduced by 3.95 GtCO2-eq giving 25.0% lower emissions than in the baseline. Around half of this potential occurs in non-OECD/EIT countries with OECD countries providing most of the remainder. f) Should just 70% of the individual power-generation shares assumed above for all the mitigation technologies be achieved by 2030, the mitigation potential would reduce to 1.69 GtCO2-eq. g) This range is in reasonable agreement with the TAR analysis potential of 1.3 to 2.5 GtCO2-eq/yr for less than 27 US$/tCO2-eq avoided (IPCC, 2001), because this potential was only out to 2020, the baseline has since been adjusted, and since the TAR was published there has been increased acceptance for improved designs of nuclear power plants, an increase in development and deployment of renewable energy technologies and a better understanding of CCS technologies.
For costs <50 US$/tCO2-eq avoided: a) Fossil-fuel generation reduces further to 13,308 TWh/yr (of which 5324 TWh/yr is from new build plants) and accounts for 42% of total generation. b) Renewable-energy generation increases to 10,673 TWh/yr by 2030 giving a 33.7% share of total generation. Solar PV and CSP are more costly (Table 4.19) so they can only offer substitution for fossil fuels above 50 US$/tCO2-eq avoided. c) Nuclear power share of total generation remains similar since other technologies now compete. d) CCS now becomes competitive and 2003 TWh/yr is generated by coal and gas-fired plants with CCS systems installed. e) Overall GHG emissions in 2030 are now reduced by 6.44 GtCO2-eq/yr below the baseline, although if only 70% of the assumed shares of total power generation for all the mitigation technologies are reached by 2030, the potential declines to 3.05 GtCO2-eq. Non-OECD/EIT countries continue to provide half of the mitigation potential. For costs <100 US$/tCO2-eq avoided: a) As more low- and zero-carbon technologies become competitive, fossil-fuel generation without CCS further reduces to 11,824 TWh in 2030 and is now only 37% of total generation. b) New renewable energy generation increases to 8481 TWh/yr by 2030, which together with the plants remaining in operation from 2010, gives a 34% share of total generation. c) New nuclear power provides 3574 TWh to give 17% of total generation. d) Coal- and gas-fired plants with CCS account for 3650 TWh/yr by 2030 or 12% of total generation. e) The overall mitigation potential of the electricity sector is 7.22 GtCO2-eq/yr which is a reduction of around 45% of GHGs below the baseline. If only 70% of the assumed shares of power generation by all low- and zero-emission technologies are achieved, then the potential would be around 45% lower at 3.97 GtCO2-eq. Non-OECD/EIT countries contribute over half the total potential. No single technological option has sufficient mitigation potential to meet the economic potential of the electricitygeneration sector. To achieve these potentials by 2030, the relatively high investment costs, the difficulties in rapidly building sufficient capacity and expertise, and the threats resulting from introducing new low-carbon technologies as perceived by the incumbents in the existing markets, will all need to be addressed. This analysis concentrates on the individual mitigation potentials for each technology at the high end of the wide range found in the literature (Figure 4.29b; IEA, 2006a; IEA, 2006b). This serves to illustrate that significant reductions in emissions from the energy-supply sector are technically and economically feasible using both the range of technology solutions currently 303
Energy Supply
Chapter 4
(a) 16
(b) GtCO2-eq per year
switching/ efficiency CCS
16
GtCO2-eq per year switching/ efficiency CCS
10
10 baseline GHG emissions from coal-, gas- and oil-fired power generation
GHG emissions by 2030 after substitution of some fossil fuel generation by nuclear and renewables, plus reduced emissions from fuel switching, plant efficiency improvements and CCS uptake.
renewables renewables nuclear
0 2004
2010
2020
2030
nuclear
0 2004
2010
2020
2030
Figure 4.29: Indicative low(a) and high(b) range estimates of the mitigation potential in the electricity sector based on substitution of existing fossil-fuel thermal power stations with nuclear and renewable energy power generation, coupled with energy-efficiency improvements in power-generation plants and transmission, including switching from coal to gas and the uptake of CCS. CHP and heat are not included, nor electricity savings from energy-efficiency measures in the building and industry sectors. Source: Based on IEA, 2006a; IEA, 2006b.
available and those close to market. Reducing the individual assumed shares of the technologies in the 2030 power generation mix by 30% gives less ambitious potentials that are closer to the lower end of the ranges found in the literature (Figure 4.29a). Energy-efficiency savings of electricity use in the buildings (Chapter 6) and industry (Chapter 7) sectors will reduce these total emissions potentials (Section 11.3.1). 4.4.4.2
Uncertainties
The wide range of energy supply-related potentials in the literature is due to the many uncertainties and assumptions involved. This analysis of the costs and mitigation potential for energy-supply technologies through to 2030 involved the following degrees of confidence. • There is high agreement on the energy types and amounts of current global and regional energy sources used in the baseline (with the exception of traditional biomass, for which data are uncertain) because the several sources of those estimates are in close agreement. • There is high agreement that energy supply will grow between now and 2030 with medium confidence in projections of the total energy demand by 2030. Most assumptions about population and energy use in various scenarios do not diverge greatly until after 2030, although past experience suggests that projections, even over a 25-year period, can be erroneous. • Estimates of specific potentials out to 2030 for electricitysupply technologies based on specific studies have only low 304
agreement that a single value can be estimated accurately. However, there is medium confidence that the true potential of a mixture of supply technologies lies somewhere within the range estimated. • The actual distribution of new technologies in 2030 can be estimated with medium confidence by using trend analyses, technology assessments, economic models and other techniques, but cannot take into account changing national policies and preferences, future carbon-price factors, and the unanticipated evolution of technologies or their cost. Current rates of adoption for particular technologies have been identified but there is low to medium agreement that these rates may continue until 2030. • Despite the methodological limitations, the future costs and technical potentials identified provide a medium confidence for considering strategies and decisions over the next several decades. The analysis falls within the range of other projections for specific technologies. 4.4.4.3
Transport biofuels
Assessments for the uptake of biofuels range between 20 and 25% of global transport road fuels by 2050 and beyond (Chapter 5). The 2006 WEO (IEA, 2006b) Reference scenario predicted biofuels will supply 4% of road fuels by 2030 with greater potential up to 7% under the Alternative Policy scenario. To achieve double this penetration, as envisaged under the Beyond Alternative Policy scenario, would avoid around 0.5GtCO2/ yr, but is likely to require large-scale introduction of
Chapter 4
Energy Supply
increasing carbon emissions from ? GtCO 2 oil shales, oil sands, heavy oils, coal-to-liquids, gas-to-liquids etc.
12 GtCO2/yr
4.5
Policies and instruments
11.6 GtCO2 1.6-3.5 GtCO2
potential emission reductions from vehicle efficiency improvements
4.5.1
Emission reduction policies
Source: Based on IEA, 2006b.
The reduction of GHG emissions from energy-supply systems is being actively pursued through a variety of government policies and private sector research. There are many technologies, behavioural changes and infrastructural developments that could be adopted to reduce the environmental impacts of current energy-supply systems (see Chapter 13). Whereas planning policies provide background for climatechange mitigation programmes, most climate policies relating to energy supply tend to come from three policy ‘families’ (OECD, 2002a): • economic instruments (e.g. subsidies, taxes, tax exemption and tax credit); • regulatory instruments (e.g. mandated targets, minimum performance standards, vehicle-exhaust emission controls); and • policy processes (e.g. voluntary agreements and consultation, dissemination of information, strategic planning).
second-generation biofuels from ligno-cellulosic conversions. Based on ETP assumptions (IEA, 2006a), the mitigation potential of biofuels by 2030 is likely to be less than from vehicle efficiency improvements (Chapter 5; Figure 4.30).
In addition, governments support RD&D programmes with financial incentives or direct investment to stimulate the development and deployment of new innovative energyconversion technologies and create markets for them (Section 4.5.6).
6
CO2 emissions due to increasing conventional oil demand up to 2030
Emissions by 2030 range between 7.1-9.4 GtCO2 plus those from unconventional liquids 0.6-1.0 GtCO2
potential emission reductions from biofuels displacing oil products
0 2002
2010
2020
2030
Figure 4.30: Potential increased emissions from the greater uptake of unconventional oils by 2030 could offset potential reductions from both biofuels and vehicleefficiency improvements, but will be subject to the future availability and price of conventional oil.
Transport emissions of 6.7 GtCO2 in 2002 will increase under business as usual to 11.6 GtCO2 by 2030, but could be reduced by efficiency improvements together with the increased uptake of biofuels to emit between 7.1 and 9.4 GtCO2 (IEA, 2006a). This mitigation potential of between 2.2 and 4.5 GtCO2, however, could be partially offset by the increased uptake of unconventional liquid fuels (Section 4.3.1.4). Their potential is uncertain as, being more costly per litre to produce, they will be dependent partly on the future oil price and level of reserves. Overall then, the emissions from transport fuels up to 2030 will probably continue to rise (Chapter 5). 4.4.4.4
Heating and cooling
The wide range of fuels and applications used for temperature modifications and the poor data base of existing heat and refrigeration plants makes the mitigation potential for heating and cooling difficult to assess. IEA (2006a) calculated the mitigation potential by 2030 for buildings (Chapter 6) of up to 2.6 GtCO2/yr, including 0.1-0.3 GtCO2/yr for solar systems, and up to 0.6 GtCO2/yr for industry (Chapter 7). The mitigation potentials of CHP and trigeneration (heating, cooling and power generation) have not been assessed here.
Many GHG emission-reduction policies undertaken to date aim to achieve multiple objectives. These include market and subsidy reform, particularly in the energy sector (Table 4.21). In addition, governments are using a variety of approaches to overcome market barriers to energy-efficiency improvements and other ‘win-win’ actions. Selecting policies and measures is not an easy task. It depends on many factors, including costs, potential capacity, the extent to which emissions must be reduced, environmental and economic impacts, rates at which the technology can be introduced, government resources available and social factors such as public acceptance. When implementing policies and measures, governments could consider the impacts of measures on other economies such as the specific needs and concerns of least developed countries arising from the adverse effects of climate change, on those nations that rely heavily on income generated from fossil-fuel exports, and on oil-importing developing countries. 4.5.1.1
Emission-reduction policies for energy supply
Subsidies, incentives and market mechanisms presently used to promote fossil fuels, nuclear power and renewables may need some redirection to achieve more rapid decarbonization of the energy supply. 305
Energy Supply
Chapter 4
Table 4.21: Examples of policy measures given general policy objectives and options to reduce GHG emissions from the energy-supply sector. Policy options Policy objectives
Policy processes Economic instruments
Regulatory instruments
Voluntary agreements
Dissemination of information and strategic planning
Technological RD&D and deployment
Energy efficiency
• Higher energy taxes • Lower energy subsidies • Power plant GHG taxes • Fiscal incentives • Tradable emissions permits
• Power plant minimum efficient standards • Best available technologies prescriptions
• Voluntary commitments to improve power plant efficiency
• Information and education campaigns.
• Cleaner power generation from fossil fuels
Energy source switching
• GHG taxes • Tradable emissions permits • Fiscal incentives
• Power plant fuel portfolio standards
• Voluntary commitments to fuel portfolio changes
• Information and education campaigns.
• Increased power generation from renewable, nuclear, and hydrogen as an energy carrier
Renewable energy
• Capital grants • Feed-in tariffs • Quota obligation and permit trading • GHG taxes • Tradable emissions permits
• Targets • Supportive transmission tariffs and transmission access
• Voluntary • Information agreements to install and education renewable energy campaigns capacity • Green electricity validation
• Increased power generation from renewable energy sources
Carbon capture and storage
• GHG taxes • Tradable emissions permits
• Emissions restrictions for major point source emitters
• Voluntary agreements to develop and deploy CCS
• Chemical and biological sequestration • Sequestration in underground geological formations
Subsidies and other incentives The effects of various policies and subsidies that support fossil-fuel use have been reviewed (IEA, 2001; OECD, 2002b; Saunders and Schneider, 2000). Government subsidies in the global energy sector are in the order of 250–300 billion US$/yr, of which around 2–3% supports renewable energy (de Moor, 2001; UNDP 2004a). An OECD study showed that global CO2 emissions could be reduced by more than 6% and real income increased by 0.1% by 2010 if support mechanisms on fossil fuels used by industry and the power-generation sector were removed (OECD, 2002b). However, subsidies are difficult to remove and reforms would need to be conducted in a gradual and programmed fashion to soften any financial hardship. For both environmental and energy-security reasons, many industrialized countries have introduced, and later increased, grant support schemes for producing electricity, heat and transport fuels based on nuclear or renewable energy resources and on installing more energy-efficient power-generation plant. For example, the US has recently introduced federal loan guarantees that could cover up to 80% of the project costs, production tax credits worth 6 billion US$, and 2 billion US$ of risk coverage for investments in new nuclear plants (Energy Policy Act, 2005). To comply with the 2003 renewable energy directive, all European countries have installed feed-in tariffs or 306
• Information campaigns
tradable permit schemes for renewable electricity (EEA, 2004; EU, 2003). Several developing countries including China, Brazil, India and a number of others have adopted similar policies. Quantitative targets Setting goals and quantitative targets for low-carbon energy at both national and regional levels increases the size of the markets and provides greater policy stability for project developers. For example, EU-15 members agreed on targets to increase their share of renewable primary energy to 12% of total energy by 2010 including electricity to 22% and biofuels to 5.75% (EU, 2001; EU 2003). The Latin American and Caribbean Initiative, signed in May 2002 included a target of 10% renewable energy by 2010 (Goldemberg, 2004). The South African Government mandated an additional 10 TWh renewable energy contribution by 2013 (being 4% of final energy consumption) to the existing contribution of 115 TWh/yr mainly from fuel wood and waste (DME, 2003). Many other countries outlined similar targets at the major renewable energy conference in Bonn (Renewables, 2004) attended by 154 governments, but not to the extent that emissions will be reduced below business as usual. Feed-in tariffs/Quota obligations Quota obligations with tradable permits for renewable
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energy and feed-in tariffs have been used in many countries to accelerate the transition to renewable energy systems (Martinot, 2005). Both policies essentially serve different purposes, but they both help promote renewable energy (Lauber, 2004). Price-based, feed-in tariffs (providing long price certainty for renewable energy producers) have been compared with quantity-based instruments, including quotas, green certificates and competitive bidding (Sawin, 2003a; Menanteau et al., 2003; Lauber, 2004). The total level of support provided for preferential power tariffs in EU-15, in particular Germany, Italy and Spain, exceeded 1 billion € in 2001 (EEA, 2004). Experience confirms that incentives to support ‘green power’ by rewarding performance are preferable to a capital investment grant, because they encourage market deployment while also promoting increases in production efficiency (Neuhoff, 2004). In terms of installed renewable energy capacity, better results have been obtained with price-based than with quantity-based approaches (EC, 2005; Ragwitz et al., 2005; Fouquet et al., 2005). In theory, this difference should not exist as bidding prices that are set at the same level as feed-in tariffs should logically give rise to comparable capacities being installed. The discrepancy can be explained by the higher certainty of current feed-in tariff schemes and the stronger incentive effect of guaranteed prices. The potential advantages offered by green certificate trading systems based on fixed quotas are encouraging a number of countries and states to introduce such schemes to meet renewable energy goals in an economically efficient way. Such systems can encourage more precise control over quotas, create competition among producers and provide incentives to lower costs (Menanteau et al., 2003). Quota-obligation systems are only beginning to have an effect on capacity additions, in part because they are still new. However, about 75% of the wind capacity installed in the US between 1998 and 2004 occurred in states with renewable energy standards. Experience shows that if certificates are delivered under long-term agreements, effectiveness and compliance can be high (Linden et al., 2005; UCS, 2005). Tradable permit systems and CDM In recent years, domestic and international tradable emission permit systems have received recognition as a means of lowering the costs of meeting climate-change targets. Creating carbon markets can help economies identify and realize economic ways to reduce GHG emissions and other energy-related pollutants, or to improve efficiency of energy use. The cost of achieving the Kyoto Protocol targets in OECD regions could fall from 0.2% of GDP without trading to 0.1% (Newman et al., 2002) as a result of introducing emission trading in an international regime. Emission trading, such as the European and CDM schemes, is designed to result in immediate GHG reductions, but CDM also has long-term aspects, since the projects must assist developing countries in achieving sustainable development (see Chapter 13). The CDM successfully registered 450 projects by
Energy Supply
the end of 2006 under the UNFCCC by the Executive Board with many more in the pipeline. Since the first project entered the pipeline in December 2003, 76% of projects belong to the energy sector. If all the 1300 projects in the pipeline at the end of 2006 are successfully registered with the UNFCCC and perform as expected, an accumulated emission reduction of more than 1400 MtCO2-eq by end of 2012 can be expected (UNEP, 2006). Information instruments Education, technical training and public awareness are essential complements to GHG mitigation policies. They provide direct and continuous incentives to think, act and buy ‘green’ energy and to use energy wisely. Green power schemes, where consumers may choose to pay more for electricity generated primarily from renewable energy sources, are an example of combining information with real choice for the consumer (Newman et al., 2002). Voluntary energy and emissions savings programmes, such as Energy Star (EPA, 2005a), Gas Star (EPA, 2005b) and Coalbed Methane Outreach (EPA, 2005c) serve to effectively disseminate relevant information and reduce knowledge barriers to the efficient and clean use of energy. These programmes include public education aspects, but are also built on industry/government partnerships. However, uncertainties on the effectiveness of information instruments for climate-change mitigation remain. More sociological research would improve the knowledge on adequacy of information instruments (Chapter 13). Technology development and deployment The need for further investments in R&D of all low-carbonemission technologies, tied with the efficient marketing of these products, is vital to climate policy. Programmes supporting ‘clean technology’ development and diffusion are a traditional focus of energy and environmental policies because energy innovations face barriers all along the energy-supply chain (from R&D, to demonstration projects, to widespread deployment). Direct government support is often necessary to hasten deployment of radically new technologies due to a lack of industry investment. This suggests that there is a role for the public sector in increasing investment directly and in correcting market and regulatory obstacles that inhibit investment in new technology through a variety of fiscal instruments such as tax deduction incentives (Energy Policy Act, 2005; Jaffe et al, 2005). Following the two oil crises in the 1970s, public expenditure for energy RD&D rose steeply, but then fell steadily in industrial countries from 15 billion US$ in 1980 to about 7 billion US$ in 2000 (2002 prices and exchange rates). Shares of IEA membercountry support for energy R&D over the period 1974–2002 were about 8% for renewable energy, 6% for fossil fuel, 18% for energy efficiency, 47% for nuclear energy and 20% on other items (IEA, 2004b). During this period, a number of national governments (e.g. US, Germany, United Kingdom, France, Spain and Italy) made major cuts in their support for energy 307
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R&D. Public spending on energy RD&D increased in Japan, Switzerland, Denmark and Finland and remained stable in other OECD countries (Goldemberg and Johannson, 2004). Technology deployment is a critical activity and learning from market experience is fundamental to the complicated process of advancing a technology toward economic efficiency while encouraging the development of large-scale, privatesector infrastructure (IEA, 2003h). This justifies new technology deployment support by governments (Section 4.5.6). 4.5.1.2
Policy implementation experiences—successes and failures
Experiences of early policy implementation in the 1990s to reduce GHG emissions exist all over the world. This section lists and evaluates some examples. The fast penetration of wind power in Denmark was due to a regulated, favourable feed-in tariff. However, a new energy act in 1999 changed the policy to one based on the trading of green certificates. This created considerable uncertainty for investors and led to a significant reduction in annual investments in wind power plants during recent years (Johansson and Turkenburg, 2004). In Germany, a comprehensive renewable energy promotion approach launched at the beginning of the 1990s led to it becoming the world leader in terms of installed wind capacity, and second in terms of installed PV capacity. The basic elements of the German approach are a combination of policy instruments, favourable feed-in tariffs and security of support to reduce investment risks (Johansson and Turkenburg, 2004). When Spain passed a feed-in law in 1994, relatively few wind turbines were in operation. By the end of 2002, the country ranked second in the world, but had less success with solar PV in spite of having high solar radiation levels and setting PV tariffs similar to those in Germany. Little PV capacity was installed initially because regulations to enable legal grid connection were not established until 2001 when national technical standards for safe grid connection were implemented. PV producers who sold electricity into the grid, including individual households, had to register as businesses in order not to pay income tax on their sales (Sawin, 2003a). Significant growth in Spanish PV manufacturing in recent years is more attributable to the neighbouring German market (Ristau, 2003). In 1990, the UK government launched the first of several rounds of competitive bidding for renewable energy contracts, known as the Non-Fossil Fuel Obligation (NFFO). The successive tendering procedures resulted in regular decreases in the prices for awarded contract value for wind and other renewable electricity projects. The average price for project proposals, irrespective of the technology involved, decreased from 0.067 €/kWh in 1994 to 0.042 €/kWh by 1998, being only 0.015 €/kWh above the wholesale electricity pool reference purchase price for the corresponding period 308
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(Menanteau et al., 2001). Due to only relatively small volumes of renewable electricity being realized through the tender process, the government changed to a support mechanism by placing an obligation on electricity suppliers to sell a minimum percentage of power from new renewable energy sources. The annual growth rate of electricity generation by eligible renewable energy plants has significantly increased since the introduction of the obligation in April 2002 (OFGEM, 2005). Swedish renewable energy policy during the 1970s and 1980s focused on strong efforts in technology research and demonstration. Subsequently market development took off during the 1990s when taxes and subsidies created favourable economic conditions for new investments and fuel switching. The use of biomass increased substantially during the 1990s (for example forest residues for district heating increased from 13 PJ in 1990 to 65 PJ in 2001). Increased carbon taxes created strong incentives for fuel switching from cheaper electric and oil-fired boiler for district heating to biomass cogeneration. The increase of biomass utilization led to development of the technology for biomass extraction from forests, production of short-rotation coppice Salix and implementation of more efficient district heating conversion technologies (Johansson, 2004). Japan launched a ‘Solar Roofs’ programme in 1994 to promote PV through low-interest loans, a comprehensive education and awareness programme and rebates for gridconnected residential systems. In 1997, the rebates were opened to owners and developers of housing complexes and Japan become the world’s largest installer of PV modules (Haas, 2002). Government promotion included publicity on television and in newspapers (IEA, 2003f). Total capacity increased at an average of more than 42% annually between 1994 and 2002 with more than 420 MW installed leading to a 75% cost reduction per Watt (Maycock, 2003; IEA, 2003f). The rebates declined gradually from 50% of installed cost in 1994 to 12% in 2002 when the programme ended. Japan is now the world’s leading manufacturer, having surpassed the US in the late 1990s. China’s State Development and Planning Commission launched a renewable energy Township Electrification Program in 2001 to provide electricity to remote rural areas by means of stand-alone renewable energy power systems. During 2002– 2004, almost 700 townships received village-scale solar PV stations of approximately 30–150 kW (about 20 MW total), of which few were hybrid systems with wind power (about 800 kW total of wind). Overall, the government provided 240 million US$ to subsidize the capital costs of equipment and around one million rural dwellers were provided with electricity from PV, wind-PV hybrid, and small hydropower systems (Martinot, 2005). Given the difficulties of other rural electrification projects using PV (ERC, 2004), it is too early to assess the effectiveness of this programme. The California expansion plan to aid the installation of a million roofs of solar power in the residential sector in the next
Chapter 4
Energy Supply
ten years was signed into law in August 2006 (Environment California, 2006). The law increased the cap on net metering from 0.5% of a utility’s load to 2.5%. A solar rebate programme will be created and it will be mandatory that solar panels become a standard option for new homebuyers. 4.5.2
Air quality and pollution
The Johannesburg Plan of Implementation (UNDESA, 2002) called on all countries to develop more sustainable consumption and production patterns. Policies and measures to promote such pathways will automatically result in a reduction of GHG emissions and be useful to control air pollution (Section 11.8). Non-toxic CO2 emissions from combustion processes have no detrimental effects on a local or regional scale, whereas toxic emissions such as SO2 and particulates can have local health impacts as well as potentially wider detrimental environmental impacts. The need for uncontaminated food and clean water to maintain general health have been recognized and addressed for a long time. However, only in recent decades has the importance of clean air to health been seriously noted (WHO, 2003). Major health problems suffered by women and children in the developing world (acute respiratory infection, chronic obstructive lung disease, cancer and pulmonary diseases) have been attributed to a lack of access to high-quality modern energy for cooking (Smith, 2002; Smith et al., 2000a; Lang et al., 2002; Bruce et al., 2000). The World Health Organisation (WHO, 2002) ranked indoor air pollution from burning solid fuels as the fourth most important health-risk factor in least developed countries where 40% of the world’s population live, and is estimated to be responsible for 2.7% of the global burden of disease (Figure 4.31). It has been estimated that half
5
g/m3
a million children and women die each year in India alone from indoor air pollution (Smith et al., 2000a). A study of indoor smoke levels conducted in Kenya revealed 24-hour average respirable particulate concentrations as high as 5526 μg/m3 compared with the EPA standards for acceptable annual levels of 50 μg/m3 (ITDG, 2003) and the EU standard for PM10 of 40 μg/m3 (European Council Directive 99/30/EC). Another comprehensive study in Zimbabwe showed that those who came from households using wood, dung or straw for cooking were more than twice as likely to have suffered from acute respiratory disease than those coming from households using LPG, natural gas or electricity (Mishra, 2003). Feasible and cost-effective solutions to poor air quality in both urban and rural areas need to be urgently identified and implemented (World Bank, 1998). Increasing access to modern energy services can help alleviate air-quality problems as well as realize a decrease in GHG emissions as greater overall efficiency is often achieved over the entire domestic energy cycle, starting from the provision of primary energy up to the eventual end-use. For instance, a shift from burning crop residues to LPG, kerosene, ethanol gel or biogas could decrease indoor air pollution by approximately 95% (Smith et al., 2000b; Sims et al, 2003b; Goldemberg et al., 2004; Larson and Yang, 2004). Policies and measures aimed at increasing sustainability through reduction of energy use, energy-efficiency improvements, switching from the use of fossil fuels, and reducing the production of process wastes, will result in a simultaneous lowering of GHG emissions and reduced air pollution. Conversely, there are cases where measures taken to improve air quality can result in a simultaneous increase in the quantity of GHGs emitted. This is most likely to occur in those developing countries experiencing a phase of strong economic growth, but where it may not be economically feasible or desirable to move rapidly away from the use of an indigenous primary energy source such as oil or coal (Brendow, 2004). Most regulations for air quality rely on limiting emissions of pollutants, often incorporating ambient air-quality guidelines or standards (Sloss et al., 2003). Although regulations to limit CO2 emissions could be incorporated as command and control clauses in most of the existing legislative schemes, no country has so far attempted to do so. Rather, emissions trading has emerged as the preferred method of effecting global GHG mitigation, both within and outside the auspices of the Kyoto Protocol (Sloss et al., 2003).
4
3
2
1
0 South Africa
Kenya Nepal China
India Gambia
WHO recommended limit = 0.12 g/m3
Figure 4.31: Indoor levels of particulate concentrations emitted from wood fuel combustion in selected developing countries Source: Karekezi and Kithyoma, 2003.
Ambient air-quality standards or guidelines are usually set in terms of protecting health or ecosystems. They are thus applicable only at or near ground level where acceptable concentrations of gaseous emissions such as SO2 can often be achieved through atmospheric dispersion using a tall stack as opposed to physical removal by scrubbers. Tall stacks avoid excessive ground-level concentrations of gaseous pollutants and 309
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are still in use at the majority of existing industrial installations and power plants around the world. If the use of tall stacks is precluded due to stringent limits being set for ambient SO2 concentrations mandate, then the alternative of SO2 scrubbers or other end-of-pipe removal equipment will require energy for its operation and thus divert it away from the production process. This leads to an overall decrease in cycle efficiency with a concomitant increase in CO2 emissions. Sorbent extraction or other processes necessary to support scrubber operations also have GHG emissions associated with them. This effectively amounts to trading off a potential local or regional acid rain problem against a larger global climate problem. The overall costs of damage due to unmitigated CO2 emissions have been estimated to greatly exceed those from regional acidification impacts arising from insufficient control of SO2 emissions (Chae and Hope, 2003). Air-quality legislation needs to be approached using the principles of integrated pollution prevention and control if unexpected and unwanted climate impacts on a global scale are to be avoided (Nalbandian, 2002). Adopting a multi-parameter approach could be useful. A US proposal calls for a cap and trade scheme for the power sector, simultaneously covering SO2, NOx, mercury and CO2, which would specifically avoid conflicts with conventional regulations. Facilities would be required to optimize control strategies across all four pollutants (Burtraw and Toman, 2000). An approach developed for Mexico City showed that linear programming, applied to a database comprising emission-reduction information derived separately for air pollutants and GHGs, could provide a useful decision support tool to analyse least-cost strategies for meeting cocontrol targets for multiple pollutants (West et al., 2004). 4.5.3
Co-benefits of mitigation policies
Mitigation policies relating to energy efficiency of plants, fuel switching, renewable energy uptake and nuclear power, may have several objectives that imply a diverse range of co-benefits. These include the mitigation of air-pollution impacts, energy-supply security (by increased energy diversity), technological innovation, reduced fuel cost, employment and reducing urban migration. Reducing GHG emissions in the energy sector yields a global impact, but the co-benefits are typically experienced on a local or regional level. The variety of co-benefits stemming from GHG mitigation policies and the utilization of new energy technologies can be an integral part of economic policies that strive to facilitate sustainable development. These include improved health, employment and industrial development, and are explored in Chapter 11. This section therefore only covers aspects specifically related to energy supply. Quantitative information remains primarily limited to health effects with many co-effects not quantified due to a lack of information. Fuel switching and the growth of energy-efficiency programmes (Swart et al., 2003) can lead to air-quality 310
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improvements and economic benefits as well as reduced GHG emissions (Beg, 2002). The relatively high capital costs for many renewable energy technologies are offset by the fuel input having minimal or zero cost and not prone to price fluctuations, as is the case with fossil fuels (Janssen, 2002). Nuclear energy shares many of the same market co-benefits as renewables (Hagen et al., 2005). Benefits of GHG mitigation may only be expected by future generations, but co-benefits are often detectable to the current generation. Co-benefits of mitigation can be important decision criteria in analyses by policymakers, but often neglected (Jochem and Madlener, 2002). There are many cases where the net co-benefits are not monetised, quantified or even identified by decision-makers and businesses. Due consideration of co-benefits can significantly influence policy decisions concerning the level and timing of GHG mitigation action. There may be significant economic advantages to the national stimulation of technical innovation and possible spillover effects, with developing countries benefiting from innovation stimulated by GHG mitigation in industrialized countries. Most aspects of co-benefits have short-term effects, but they support long-term mitigation policies by creating a central link to sustainable development objectives (Kessels and Bakker, 2005). To date, most analyses have calculated GHG mitigation costs by dividing the incremental costs of ‘mitigation technologies’ by the amount of GHG avoided. This implicitly attributes all the costs to GHG-emission reduction and the co-benefits are seen as ancillary. Ideally, one would attribute the incremental costs to the various co-benefits by attempting to weight them. This could lead to significantly lower costs of GHG reductions since the other co-benefits would carry a share of the costs together with a change in the cost ranking of mitigation options (Schlamadinger et al. 2006). The reduced costs of new technologies due to experience, and the incentives for further improvement due to competition, can be co-benefits of climate-change policies (Jochem and Madlener, 2002). New energy technologies are typically more expensive during their market-introduction phase but substantial learning experience can usually be achieved to reduce costs and enhance skill levels (Barreto, 2001; Herzog et al., 2001; IEA, 2000; McDonald and Schrattenholzer, 2001; NCOE, 2004). Increased net employment and trade of technologies and services are useful co-benefits given high unemployment in many countries. Employment is created at different levels, from research and manufacturing to distribution, installation and maintenance. Renewable-energy technologies are more labour-intensive than conventional technologies for the same energy output (Kamman et al., 2004). For example, solar PV generates 5.65 person-years of employment per 1 million US$ investment (over ten years) and the wind-energy industry 5.7 person-years. In contrast, every million dollars invested in the coal industry generates only 3.96 person-years of employment over the same time period (Singh and Fehrs, 2001). In South Africa, the development of renewable energy technologies
Chapter 4
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could lead to the creation of over 36,000 direct jobs by 2020 (Austin et al., 2003) while more than 900,000 new jobs could be created across Europe by 2020 as a result of the increased use of renewable energy (EUFORES, 2004). 4.5.4
Implications of energy supply on sustainable development
The connection between climate-change mitigation and sustainable development is covered extensively in Chapter 12. The impact of the mitigation efforts from the energy-supply sector can be illustrated using the taxonomy of sustainability criteria and the indicators behind it. An analysis of the sustainability indicators mentioned in 750 project design documents submitted for validation under the CDM up to the end of 2005 (Olsen and Fenhann, 2006) indicated renewable energy projects provide the most sustainable impacts. Examples include biomass energy to create employment; geothermal and hydro to give a positive balance of payment; fossil-fuel switching to reduce emissions of SO2 and NOx; coal bed methane capture to reduce the number of explosions/accidents; and solar PV to create improved and increased access to electricity, employment, welfare and better learning possibilities. 4.5.4.1
Health and environment
Energy interlinks with health in two contradictory ways. It is essential to support the provision of health services, but energy conversion and consumption can have negative health impacts (Section 11.8). For example, in the UK, a lack of insufficient home heating has been identified as a principal cause of high levels of winter deaths (London Health Commission, 2003), but emissions from oil, gas, wood and coal combustion can add to reduced air quality and respiratory diseases. The historical dilemma between energy supply and health can be demonstrated for various sectors, although it should be noted that recent times have seen major improvements. For instance, whereas epidemiological studies have shown that oil production in developed countries is not accompanied by significant health risks due to application of effective abatement technology, a Kazakhstan study compared the health costs between the city of Atyrau (with a high rate of pollution from oil extraction) and Astana (without). Health costs per household in Atyrau were twice as high as in Astana. The study also showed that the annual benefits of investments in abatement technologies were at least five times higher than the virtual annual abatement costs. A key barrier to investment in abatement technologies was the differentiated responsibility, as household health costs are borne by individuals, while the earnings from oil extraction accrue to the local authorities (Netalieva et al., 2005). Accidental spills during oil-product transportation are damaging to the environment and health. There have been many spills at sea resulting in the destruction of fauna and flora, but the frequency of such incidents has declined sharply in recent
times (Huijer, 2005). There are also spills originating from cracks in pipelines due to failure or sabotage. For example, it was estimated that the trans-Ecuadorian pipeline alone has spilt 400,000 litres of crude oil since it opened in 1972. Spills at oil refineries are also not uncommon. Verweij (2003) reported that in South Africa more than one million litres of petrol leaked from the refinery pipeline systems into the soil in 2001, thus contaminating ground water. One of the most recent oil spills occurred in Nanchital, Mexico in December 2004, where it was estimated that 5000 barrels of crude oil spilled from the pipeline with much of it going into the Coatzacoalcos River. Pemex, the company owning the pipeline, indicated a willingness to compensate the more than 250 local fishermen and the owners of the 200 hardest-hit homes. Coal mining is also hazardous with many thousands of fatalities each year. Exposure to coal dust has also been associated with accelerated loss of lung function (Beeckman and Wang, 2001). 4.5.4.2
Equity and shared responsibility
Economies with a high dependence on oil exports tend to have a poorer economic performance (Leite and Weidmann, 1999). The local energy needs of the host countries may be overlooked by their governments in the quest for foreign earnings from energy exports. Inadequate returns to the energy resource-rich communities have resulted in organized resistance against oil-extraction companies. Insecurities associated with oil supplies also result in high military expenditure as shown by OPEC countries (Karl and Gary, 2004). The advent of reform in the energy sector increases inequalities. Notably electricity tariffs have generally shifted upwards after commencement of reforms (Wamukonya, 2003; Dubash, 2003) making electricity even more inaccessible to the lower-income earners. There are many genuine efforts to address such issues (World Bank, 2005), although much still needs to be done (Lort-Phillips and Herringshaw, 2006). Companies whose origin countries have stringent mandatory disclosure requirements are reported to perform best on transparency. Public private partnerships in developing countries are starting to make inroads into the issue of inequity and to harmonize practices between the developed and developing world. One such example is the Global Gas Flaring Reduction Partnership (World Bank, 2004a) aimed at reducing wasteful flaring and conserving the hydrocarbon resources for utilization by the host country. 4.5.4.3
Barriers to providing energy sources for sustainable development
The high investment cost required to build energy-system infrastructure is a major barrier to sustainable development. The IEA (2004a) estimated that 5 trillion US$ will be needed to meet electricity demand in developing countries by 2030. To meet all the eight Millennium Development Goals will require an annual average investment of 20 billion US$ to develop energy 311
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infrastructure and deliver energy services (UNDP, 2004b). Access to finance for investment in energy systems, especially in developing countries, has, nonetheless, been declining. Available infrastructure also dictates energy types and use patterns. For instance, in a study on Peruvian household demand for clean fuels, Jack (2004) found that urban dwellers were more likely to use clean fuels than rural householders, due to the availability of the necessary infrastructure. Investment costs necessary to capture natural gas and divert it into energy systems and curb flaring and venting are a barrier, even though efforts are being made to overcome this problem (World Bank, 2004a). It is estimated that over 110 billion m3 of natural gas are flared and vented worldwide annually, equivalent to the total annual gas consumption of France and Germany (ESMAP, 2004). Levels of investment vary across regions, with the most needy receiving the least resources. Between 1990 and 2001, private investments to developing and transition countries for power projects were about 207 billion US$. Nearly 43% went to Latin America and the Caribbean, 33% to East Asia and the Pacific and approximately 1.5% to sub-Saharan Africa (Kessides, 2004). Accessibility and affordability of clean fuels remains a major barrier in many developing countries, exacerbated when complex supply systems are required that lead to high transaction costs. Corruption, bureaucracy and mismanagement of energy resources have often prevented the use of proceeds emanating from extraction of energy resources from being used to provide local energy systems to meet sustainable development needs. Forms of corruption have encompassed such schemes as: • the granting of lucrative power purchase agreements (PPAs) by politicians, who then benefit from receiving a share of guaranteed prices considerably higher than the international market price (Shorrock, 2002; Vallete and Wysham, 2002); • suspending plant operations, thereby compromising access to electricity and persuading government agencies to pay high premiums for political risk insurance (Hall and Lobina, 2004); and • granting of lucrative sole-supplier trading rights for gas supplies (Lovei and McKechnie, 2000). Oil-backed loans have contributed to high foreign debts in many oil-producing countries at the expense of the poor majority (IMF, 2001; Global Witness, 2004). Despite heavy debts, such countries continue to sign for such loans (AEI, 2003) and potential revenues are used as collateral to finance government external debt rather than to reduce poverty or promote sustainable development. These loans are typically provided at higher interest rates than conventional concessionary loans (World Bank, 2004b) and so the majority of the local population fail to benefit from high oil prices (IRIN, 2004). The problem could be overcome by legal frameworks that enable the channelling of revenue into investments that provide energy 312
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systems and promote sustainable development in communities affected by energy-resource extraction. In the meantime, the problem remains a key barrier to sustainable development and, although several countries including Peru, Nigeria and Gabon have mandated enabling mechanisms for such transfers, progress in implementing these measures has been slow (Gary and Karl, 2003). Poor policies in the international financing sector hinder the establishment of energy systems for sustainable development. A review of the extractive industries (World Bank, 2004b), for example, revealed that the World Bank group and the International Finance Corporation (IFC) have been investing in oil- and gas-extractive activities that have negative impacts on poverty alleviation and sustainable development. The review, somewhat controversially, recommended that the banks should pull out of oil, gas and coal projects by 2008. Population growth and higher per-capita energy demand are forcing the transition of supply patterns from potentially sustainable systems to unsustainable ones. Efficient use of biomass can reduce CO2 emissions, but can only be sustained if supplies are adequate to satisfy demand without depleting carbon stocks by deforestation (Section 4.3.3.3). If supplies are inadequate, it may be necessary to shift demand to fossil fuels to prevent overharvesting. In Niger, for example, despite the concerted efforts through a long-term World Bank funded project, it is not possible to provide sufficient woody biomass on a sustainable basis. As a result, the government has launched a campaign to encourage consumers, particularly industry, to shift from wood to coal and has re-launched a 3000 t/yr production unit, distributed 300 t of coal to Niamey, and produced 3800 coal-burning stoves (ISNA, 2004). Further, in the electricity sector, PPAs that are not favourable to the establishment of generation plants that promote sustainable development are increasingly common. These include long-term PPAs with payments made in foreign currency denominations, leaving the power sector extremely vulnerable to macro-economic shocks as demonstrated by the 1998 Asian crisis (Wamukonya, 2003). 4.5.4.4
Strategies for providing energy for sustainable development
Although the provision of improved energy services is not mentioned specifically in the formal Millennium Development Goals (MDGs) framework, it is a vital factor. Electrification and other energy-supply strategies should target income generation if they are to be economically sustainable. It is important to focus on improving productive uses of energy as a way of contributing to income generation by providing services and not as an end in themselves. It has been argued that the traditional top-down approaches to reform the power sector – motivated by macroeconomic factors and not aimed at improving access for the poor – should be replaced by bottomup ones with communities at the centre of the decision process (GNESD, 2006).
Chapter 4
4.5.5
Energy Supply
Vulnerability and adaptation
It is essential to look at how the various components of the energy-supply chain might be affected by climate change. At the same time, it is desirable to assess current adaptation measures and their adequacy to handle potential vulnerability. A robust predictive skill is required to ensure that any mitigation programmes adopted now will still function adequately if altered climatic conditions prevail in the future. Official aid investments in developing countries are often more focused on recovery from disaster than on the creation of adaptive capacity. Lending agencies and donors will need to reform their investment policies accordingly to mitigate this problem (Monirul, 2004). Many developing countries are particularly vulnerable to extremes of normal climatic variability that are expected to be exacerbated by climate change. Assessing the vulnerability of energy supply to climatic events and longerterm climate change needs to be country- or region-specific. The magnitude and frequency of extreme weather events such as ice storms, tornadoes and cyclones is predicted to change, as may annual rainfall, cloud cover and sunshine hours. This is likely to increase the vulnerability of the various components of the energy-supply infrastructure such as transmission lines and control systems. Sea-level rise, tropical cyclones and large ocean waves may hamper offshore oil and gas exploration and extraction of these fossil fuels. Higher ambient temperatures may affect the efficiency and capacity ratings of fossil-fuel-powered combustion turbines. In addition, electricity transmission losses may increase due to higher ambient temperatures. Renewableenergy systems may be adversely affected (Sims, 2003), for example if solar power generation and water heating are impacted by increased cloud cover. Lower precipitation and higher evaporation due to higher ambient temperatures may cause lower water levels in storage lakes or rivers that will affect the outputs of hydro-electric power stations. Energy crop yields could be reduced due to new pests and weather changes and more extreme storm events could damage wind turbines and ocean energy devices. The need to take measures to lessen the impacts on energy systems resulting from their intrinsic vulnerability to climate change will remain a challenge for the foreseeable future. 4.5.6
Technology Research, Development, Demonstration, plus Deployment (RD3)
• the quantities of GHGs emitted for the rest of this century; and • achievement, or otherwise, of GHG stabilization concentration levels. Technology can play an important role in reducing the energy intensity of an economy (He and Zhang, 2006; He et al., 2006). In addition to new and improved energy-conversion technologies, such concepts as novel supply structures, distributed energy systems, grid optimization techniques, energy transport and storage methods, load management, co-generation and community-based services will have to be developed and improved (Luther, 2004). The knowledge base required to transform the energy supply and utilization system will then need to be created and expanded. Major innovations that will shape society will require a foundation of strong basic research (Friedman, 2003). Areas of generic scientific research in material-, chemical-, bio-, and geo-sciences that could be particularly important to energy supply need to be reviewed. Progress in basic research could lead to new materials and technologies that can radically reduce costs or reveal new approaches to providing energy services. For example, the development of fibre optics from generic research investment resulted in their current use to extract greater volumes of oil or gas from a reservoir than had been previously possible. Cross-disciplinary collaborations between many scientific areas, including applied research and social science, are needed for successful introduction of new energy supply and end-use technologies necessary to combat the unprecedented challenge of supporting human growth and progress while protecting global and local environments. Integrating scientific progress into energy and environmental policies is difficult and has not always received the attention it deserves (IEA, 2003a). Successful introduction of new technologies into the market requires careful coordination with governments to encourage, or at least not to hinder, their introduction. There is no single area of research that will secure a reliable future supply of energy. A diverse range of energy sources will be utilized and hence a broad range of fundamental research will be needed. Setting global priorities for technology development should be based on quantitative assessments of possible emissions and their abatement paths, but guidelines would first need to be developed (OECD, 2006a). 4.5.6.1
• • • • •
Future investments in RD3 will, in part, determine: future security of energy supplies; accessibility, availability and affordability of desired energy services; attainment of sustainable development; free-market distribution of energy supplies to all countries; deployment of low-carbon energy carriers and conversion technologies;
Public and private funding
Almost all (98%) of total OECD energy R&D investment has been by only ten IEA member countries (Margolis and Kammen, 1999; WEC, 2001). The amount declined by 50% between the peak of 1980 (following the oil price shocks) and 2002 in real terms (Figure 4.32). Expenditure on nuclear technologies, integrated over time, has been many times higher than investment in renewable energies. The end of the cold 313
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(a)
(b)
2500
US$ million (2004 prices and exchange rates)
US$ at 2004 prices and exchange rates 7 6
2000
5 Hydro Geothermal 4 Biomass Ocean 3 Wind Solar thermal-electric Solar photovoltaic 2 Solar heating and cooling
1500
1000
500
1
1975
1980
1985
1990
1995
2000 2003
Sw i tz er Ne Den land the ma rl rk Swand e s No den r Fin way Ge la rm nd Au any st Un ite Jap ria d S an tat e Ita s Un Sp ly ite C ai d an n Lu Kin ada g Ne xem dom w bo Ze ur al g G and Au reec s tr e Fr alia Be ance Po lgium rtu Ir g a Huelan l ng d Tu ary Cz rk ec h R Kor ey ep ea ub lic
0
0
Figure 4.32: IEA member government budgets for total renewable energy R&D annual investments for 1974–2003 (left, a) and investment per capita, averaged between 1990 and 2003 (right, b). Source: IEA, 2006d.
war and lower fossil-fuel prices decreased the level of public attention on energy planning in the 1980s, and global energy R&D investment has yet to return to these levels despite growing concerns about energy security and climate change (Chapter 13). Ultimately, it is only by creating a demand-pull market (rather than supply-push) that technological development, learning from experience, economies of scale in production and related cost reductions can result. As markets expand and new industries grow (the wind industry for example), more private investment in R&D results, which is often more successful than public research (Sawin, 2003b). The private sector invests a significant amount in energy RD3 to seek competitive advantage through improved technology and risk avoidance in relation to commercialization. Firms tend to focus on incremental technology improvements to gain profits in the short term. R&D spending by firms in the energy industry is particularly low with utilities investing only 1% of total sales in US, UK and the Netherlands compared with the 3% R&D-to-sales ratio for manufacturing, and up to 8% for pharmaceutical, computer and communication industries. If government policies relating to strategic research can ensure long-term markets for new technologies, then industries can see their potential, perform their own R&D and complement public research institutions (Luther, 2004). Fixed pricing laws to encourage the uptake of new energysupply technologies have been successful but do not usually result in novel concepts. Further innovation is encouraged once 314
manufacturers and utilities begin to generate profits from a new technology. They then invest more in R&D to lower costs and further increase profit margins (Menanteau et al., 2003). Under government mandatory quota systems (as used to stimulate renewable energy projects in several countries – Section 4.5.1), consumers tend to benefit the most and hence producers receive insufficient profit to invest in R&D. Recent trends in both public and private energy RD3 funding indicate that the role of ‘technology push’ in reducing GHG emissions is often overvalued and may not be fully understood. Subsidies and externalities (both social and environmental) affect energy markets and tend to support conventional sources of energy. Intervention to encourage R&D and adoption of renewable energy technologies, together with private investment and the more intelligent use of natural and social sciences is warranted (Hall and Lobina, 2004). Obtaining a useful balance between public and private research investment can be achieved by using partnerships between government, research institutions and firms. Current levels of public and private energy-supply R&D investment are unlikely to be adequate to reduce global GHG emissions while providing the world with the energy needs of the developing nations (Edmonds and Smith, 2006). Success in long-term energy-supply R&D is associated with near-term investments to ensure that future energy services are delivered cost-effectively and barriers to implementation are identified and removed. Sustainable development and providing access to modern energy services for the poor have added challenges to R&D investment (IEA, 2004a; IEA 2006a; Chapter 13).
Chapter 4
Energy Supply
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5 Transport and its infrastructure Coordinating Lead Authors: Suzana Kahn Ribeiro (Brazil), Shigeki Kobayashi (Japan)
Lead Authors: Michel Beuthe (Belgium), Jorge Gasca (Mexico), David Greene (USA), David S. Lee (UK), Yasunori Muromachi (Japan), Peter J. Newton (UK), Steven Plotkin (USA), Daniel Sperling (USA), Ron Wit (The Netherlands), Peter J. Zhou (Zimbabwe)
Contributing Authors: Hiroshi Hata (Japan), Ralph Sims (New Zealand), Kjell Olav Skjolsvik (Norway)
Review Editors: Ranjan Bose (India), Haroon Kheshgi (USA)
This chapter should be cited as: Kahn Ribeiro, S., S. Kobayashi, M. Beuthe, J. Gasca, D. Greene, D. S. Lee, Y. Muromachi, P. J. Newton, S. Plotkin, D. Sperling, R. Wit, P. J. Zhou, 2007: Transport and its infrastructure. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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Table of Contents Executive Summary ................................................... 325 5.1
Introduction ..................................................... 328
5.2
Current status and future trends ................ 328
5.3
5.4
324
5.5
Policies and measures ..................................... 366 5.5.1
Surface transport ............................................... 366
5.5.2
Aviation and shipping ......................................... 375
5.5.3
Non-climate policies........................................... 378
5.2.1
Transport today .................................................. 328
5.5.4
Co-benefits and ancillary benefits ...................... 378
5.2.2
Transport in the future ....................................... 330
5.5.5
Sustainable Development impacts of mitigation options and considerations on the link of adaptation with mitigation. ................................ 379
Mitigation technologies and strategies ...... 335 5.3.1
Road transport ................................................... 336
5.3.2
Rail...................................................................... 351
5.3.3
Aviation ............................................................... 352
5.3.4
Shipping ............................................................ 356
Mitigation potential ....................................... 357 5.4.1
Available worldwide studies ............................... 357
5.4.2
Estimate of world mitigation costs and potentials in 2030 .............................................. 359
5.6
Key uncertainties and gaps in knowledge.......................................................... 380
References..................................................................... 380
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Transport and its infrastructure
EXECUTIVE SUMMARY Transport activity, a key component of economic development and human welfare, is increasing around the world as economies grow. For most policymakers, the most pressing problems associated with this increasing transport activity are traffic fatalities and injuries, congestion, air pollution and petroleum dependence. These problems are especially acute in the most rapidly growing economies of the developing world. Mitigating greenhouse gas (GHG) emissions can take its place among these other transport priorities by emphasizing synergies and co-benefits (high agreement, much evidence). Transport predominantly relies on a single fossil resource, petroleum that supplies 95% of the total energy used by world transport. In 2004, transport was responsible for 23% of world energy-related GHG emissions with about three quarters coming from road vehicles. Over the past decade, transport’s GHG emissions have increased at a faster rate than any other energy using sector (high agreement, much evidence). Transport activity will continue to increase in the future as economic growth fuels transport demand and the availability of transport drives development, by facilitating specialization and trade. The majority of the world’s population still does not have access to personal vehicles and many do not have access to any form of motorized transport. However, this situation is rapidly changing. Freight transport has been growing even more rapidly than passenger transport and is expected to continue to do so in the future. Urban freight movements are predominantly by truck, while international freight is dominated by ocean shipping. The modal distribution of intercity freight varies greatly across regions. For example, in the United States, all modes participate substantially, while in Europe, trucking has a higher market share (in tkm1), compared to rail (high agreement, much evidence). Transport activity is expected to grow robustly over the next several decades. Unless there is a major shift away from current patterns of energy use, world transport energy use is projected to increase at the rate of about 2% per year, with the highest rates of growth in the emerging economies, and total transport energy use and carbon emissions is projected to be about 80% higher than current levels by 2030 (medium agreement, medium evidence). There is an ongoing debate about whether the world is nearing a peak in conventional oil production that will require a significant and rapid transition to alternative energy resources. There is no shortage of alternative energy sources, including oil sands, shale oil, coal-to-liquids, biofuels, electricity and 1
hydrogen. Among these alternatives, unconventional fossil carbon resources would produce less expensive fuels most compatible with the existing transport infrastructure, but lead to increased carbon emissions (medium agreement, medium evidence). In 2004, the transport sector produced 6.3 GtCO2 emissions (23% of world energy-related CO2 emissions) and its growth rate is highest among the end-user sectors. Road transport currently accounts for 74% of total transport CO2 emissions. The share of non-OECD countries is 36% now and will increase rapidly to 46% by 2030 if current trends continue (high agreement, much evidence). The transport sector also contributes small amounts of CH4 and N2O emissions from fuel combustion and F-gases (fluorinated gases) from vehicle air conditioning. CH4 emissions are between 0.1–0.3% of total transport GHG emissions, N2O between 2.0 and 2.8% (based on US, Japan and EU data only). Worldwide emissions of F-gases (CFC-12+HFC134a+HCFC-22) in 2003 were 0.3–0.6 GtCO2-eq, about 5–10% of total transport CO2 emissions (medium agreement, limited evidence). When assessing mitigation options it is important to consider their lifecycle GHG impacts. This is especially true for choices among alternative fuels but also applies to a lesser degree to the manufacturing processes and materials composition of advanced technologies. Electricity and hydrogen can offer the opportunity to ‘de-carbonise’ the transport energy system although the actual full cycle carbon reduction depends upon the way electricity and hydrogen are produced. Assessment of mitigation potential in the transport sector through the year 2030 is uncertain because the potential depends on: • World oil supply and its impact on fuel prices and the economic viability of alternative transport fuels; • R&D outcomes in several areas, especially biomass fuel production technology and its sustainability in massive scale, as well as battery longevity, cost and specific energy. Another problem for a credible assessment is the limited number and scope of available studies of mitigation potential and cost. Improving energy efficiency offers an excellent opportunity for transport GHG mitigation through 2030. Carbon emissions from ‘new’ light-duty road vehicles could be reduced by up to 50% by 2030 compared to currently produced models, assuming continued technological advances and strong policies to ensure that technologies are applied to increasing fuel economy rather than spent on increased horsepower and vehicle mass. Material substitution and advanced design could reduce the weight of light-duty vehicles by 20–30%. Since the TAR (Third Assessment Report), energy efficiency of road vehicles has improved by the market success of cleaner directinjection turbocharged (TDI) diesels and the continued market penetration of numerous incremental efficiency technologies.
ton-km, “ton” refers to metric ton, unless otherwise stated.
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Hybrid vehicles have also played a role, though their market penetration is currently small. Reductions in drag coefficients of 20–50% seem achievable for heavy intercity trucks, with consequent reductions in fuel use of 10–20%. Hybrid technology is applicable to trucks and buses that operate in urban environments, and the diesel engine’s efficiency may be improved by 10% or more. Prospects for mitigation are strongly dependent on the advancement of transport technologies. There are also important opportunities to increase the operating efficiencies of transport vehicles. Road vehicle efficiency might be improved by 5–20% through strategies such as eco-driving styles, increased load factors, improved maintenance, in-vehicle technological aids, more efficient replacement tyres, reduced idling and better traffic management and route choice (medium agreement, medium evidence). The total mitigation potential in 2030 of the energy efficiency options applied to light duty vehicles would be around 0.7–0.8 GtCO2-eq in 2030 at costs <100 US$/tCO2. Data is not sufficient to provide a similar estimate for heavy-duty vehicles. The use of current and advanced biofuels would give an additional reduction potential of another 600–1500 MtCO2-eq in 2030 at costs <25 US$/tCO2 (low agreement, limited evidence). Although rail transport is one of the most energy efficient modes today, substantial opportunities for further efficiency improvements remain. Reduced aerodynamic drag, lower train weight, regenerative breaking and higher efficiency propulsion systems can make significant reductions in rail energy use. Shipping, also one of the least energy intensive modes, still has some potential for increased energy efficiency. Studies assessing both technical and operational approaches have concluded that energy efficiency opportunities of a few percent to up to 40% are possible (medium agreement, medium evidence). Passenger jet aircraft produced today are 70% more fuel efficient than the equivalent aircraft produced 40 years ago and continued improvement is expected. A 20% improvement over 1997 aircraft efficiency is likely by 2015 and possibly 40 to 50% improvement is anticipated by 2050. Still greater efficiency gains will depend on the potential of novel designs such as the blended wing body, or propulsion systems such as the unducted turbofan. For 2030 the estimated mitigation potential is 150 MtCO2 at carbon prices less than 50 US$/tCO2 and 280 MtCO2 at carbon prices less than 100 US$/tCO2 (medium agreement, medium evidence). However, without policy intervention, projected annual improvements in aircraft fuel efficiency of the order of 1–2%, will be surpassed by annual traffic growth of around 5% each year, leading to an annual increase of CO2 emissions of 3–4% per year (high agreement, much evidence). Biofuels have the potential to replace a substantial part but not all petroleum use by transport. A recent IEA analysis 2
US term for petrol.
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estimates that biofuels’ share of transport fuel could increase to about 10% in 2030. The economic potential in 2030 from biofuel application is estimated at 600–1500 MtCO2-eq/yr at a cost of <25 US$/tCO2-eq. The introduction of flexfuel vehicles able to use any mixture of gasoline2 and ethanol rejuvenated the market for ethanol as a motor fuel in Brazil by protecting motorists from wide swings in the price of either fuel. The global potential for biofuels will depend on the success of technologies to utilise cellulose biomass (medium agreement, medium evidence). Providing public transports systems and their related infrastructure and promoting non-motorised transport can contribute to GHG mitigation. However, local conditions determine how much transport can be shifted to less energy intensive modes. Occupancy rates and primary energy sources of the transport mode further determine the mitigation impact. The energy requirements for urban transport are strongly influenced by the density and spatial structure of the built environment, as well as by location, extent and nature of transport infrastructure. If the share of buses in passenger transport in typical Latin American cities would increase by 5–10%, then CO2 emissions could go down by 4–9% at costs of the order of 60–70 US$/ tCO2 (low agreement, limited evidence). The few worldwide assessments of transport’s GHG mitigation potential completed since the TAR indicate that significant reductions in the expected 80% increase in transport GHG emission by 2030 will require both major advances in technology and implementation via strong, comprehensive policies (medium agreement, limited evidence). The mitigation potential by 2030 for the transport sector is estimated to be about 1600–2550 MtCO2 for a carbon price less than 100 US$/tCO2. This is only a partial assessment, based on biofuel use throughout the transport sector and efficiency improvements in light-duty vehicles and aircraft and does not cover the potential for heavy-duty vehicles, rail transport, shipping, and modal split change and public transport promotion and is therefore an underestimation. Much of this potential appears to be located in OECD North America and Europe. This potential is measured as the further reduction in CO2 emissions from a Reference scenario, which already assumes a substantial use of biofuels and significant improvements in fuel efficiency based on a continuation of current trends. This estimate of mitigation costs and potentials is highly uncertain. There remains a critical need for comprehensive and consistent assessments of the worldwide potential to mitigate transport’s GHG emissions (low agreement, limited evidence). While transport demand certainly responds to price signals, the demand for vehicles, vehicle travel and fuel use are significantly price inelastic. As a result, large increases in prices or taxes are required to make major changes in GHG emissions.
Chapter 5
Many countries do heavily tax motor fuels and have lower rates of fuel consumption and vehicle use than countries with low fuel taxes (high agreement, much evidence). Fuel economy regulations have been effective in slowing the growth of GHG emissions, but so far growth of transport activity has overwhelmed their impact. They have been adopted by most developed economies as well as key developing economies, though in widely varying form, from uniform, mandatory corporate average standards, to graduated standards by vehicle weight class or size, to voluntary industry-wide standards. The overall effectiveness of standards can be significantly enhanced if combined with fiscal incentives and consumer information (medium agreement, medium evidence). A wide array of transport demand management (TDM) strategies have been employed in different circumstances around the world, primarily to manage traffic congestion and reduce air pollution. TDMs can be effective in reducing private vehicle travel if rigorously implemented and supported (high agreement, low evidence). In order to reduce emissions from air and marine transport resulting from the combustion of bunker fuels, new policy frameworks need to be developed. However ICAO endorsed
Transport and its infrastructure
the concept of an open, international emission trading system for the air transport sector, implemented through a voluntary scheme, or incorporation of international aviation into existing emission trading systems. Environmentally differentiated port dues are being used in a few places. Other policies to affect shipping emissions would be the inclusion of international shipping in international emissions trading schemes, fuel taxes and regulatory instruments (high agreement, much evidence). Since currently available mitigation options will probably not be enough to prevent growth in transport’s emissions, technology research and development is essential in order to create the potential for future, significant reductions in transport GHG emissions. This holds, amongst others, for hydrogen fuel cell, advanced biofuel conversion and improved batteries for electric and hybrid vehicles (high agreement, medium evidence). The best choice of policy options will vary across regions. Not only levels of economic development, but the nature of economic activity, geography, population density and culture all influence the effectiveness and desirability of policies affecting modal choices, infrastructure investments and transport demand management measures (high agreement, much evidence).
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5.1 Introduction
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Table 5.1: World transport energy use in 2000, by mode Mode
Mobility is an essential human need. Human survival and societal interaction depend on the ability to move people and goods. Efficient mobility systems are essential facilitators of economic development. Cities could not exist and global trade could not occur without systems to transport people and goods cheaply and efficiently (WBCSD, 2002). Since motorized transport relies on oil for virtually all its fuel and accounts for almost half of world oil consumption, the transport sector faces a challenging future, given its dependence on oil. In this chapter, existing and future options and potentials to reduce greenhouse gases (GHG) are assessed. GHG emission reduction will be only one of several key issues in transport during the coming decades and will not be the foremost issue in many areas. In developing countries especially, increasing demand for private vehicles is outpacing the supply of transport infrastructure – including both road networks and public transit networks. The result is growing congestion and air pollution,3 and a rise in traffic fatalities. Further, the predominant reliance on private vehicles for passenger travel is creating substantial societal strains as economically disadvantaged populations are left out of the rapid growth in mobility. In many countries, concerns about transport will likely focus on the local traffic, pollution, safety and equity effects. The global warming issue in transport will have to be addressed in the context of the broader goal of sustainable development.
5.2 Current status4 and future trends 5.2.1
Transport today
The transport sector plays a crucial and growing role in world energy use and emissions of GHGs. In 2004, transport energy use amounted to 26% of total world energy use and the transport sector was responsible for about 23% of world energy-related GHG emissions (IEA, 2006b). The 1990–2002 growth rate of energy consumption in the transport sector was highest among all the end-use sectors. Of a total of 77 EJ5 of total transport energy use, road vehicles account for more than three-quarters, with light-duty vehicles and freight trucks having the lion’s share (see Table 5.1). Virtually all (95%) of transport energy comes from oil-based fuels, largely diesel (23.6 EJ, or about 31% of total energy) and gasoline (36.4 EJ, 47%). One consequence of this dependence, coupled with the only moderate differences in carbon content of the various 3 4 5
Light-duty vehicles (LDVs) 2-wheelers Heavy freight trucks
Energy use (EJ)
Share (%)
34.2
44.5
1.2
1.6
12.48
16.2
Medium freight trucks
6.77
8.8
Buses
4.76
6.2
Rail
1.19
1.5
Air
8.95
11.6
Shipping
7.32
9.5
76.87
100
Total Source: WBCSD, 2004b.
oil-based fuels, is that the CO2 emissions from the different transport sub-sectors are approximately proportional to their energy use (Figure 5.1). Economic development and transport are inextricably linked. Development increases transport demand, while availability of transport stimulates even more development by allowing trade and economic specialization. Industrialization and growing specialization have created the need for large shipments of goods and materials over substantial distances; accelerating globalization has greatly increased these flows. Urbanization has been extremely rapid in the past century. About 75% of people in the industrialized world and 40% in the developing world now live in urban areas. Also, cities have grown larger, with 19 cities now having a population over 10 million. A parallel trend has been the decentralization of cities – they have spread out faster than they have grown in population, with rapid growth in suburban areas and the rise of ‘edge cities’ in the outer suburbs. This decentralization has created both a growing demand for travel and an urban pattern that is not easily served by public transport. The result has been a rapid increase in personal vehicles – not only cars but also 2-wheelers – and a declining share of transit. Further, the lower-density development and the greater distances needed to access jobs and services have seen the decline of walking and bicycling as a share of total travel (WBCSD, 2002). Another crucial aspect of our transport system is that much of the world is not yet motorized because of low incomes. The majority of the world’s population does not have access to personal vehicles, and many do not even have access to motorized public transport services of any sort. Thirty-three percent of China’s population and 75% of Ethiopia’s still did not have access to all-weather transport (e.g., with roads passable
Although congestion and air pollution are also found in developed countries, they are exacerbated by developing country conditions. The primary source for the ‘current status’ part of this discussion is WBCSD (World Business Council for Sustainable Development) Mobility 2001 (2002), prepared by Massachusetts Institute of Technology and Charles River Associates Incorporated. 83 EJ in 2004 (IEA, 2006b).
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2500
Transport and its infrastructure
Mtoe
6
Gt CO2
1500
NonOECD
Non-Road
4
NonOECD
Non-Road 2000
Road
Road Non-Road 1000
Non-Road
0 1971
OECD
OECD
500
2
Road
Road
1980
1990
2000
0 1971
1980
1990
2000
Figure 5.1: Energy consumption and CO2 emission in the transport sector Source: IEA, 2006c,d
most of the year). Walking more than 10 km/day6 each way to farms, schools and clinics is not unusual in rural areas of the developing world, particularly sub-Saharan Africa, but also in parts of Asia and Latin America. Commuting by public transport is very costly for the urban poor, taking, for example, 14% of the income of the poor in Manila compared with 7% of the income of the non-poor (World Bank, 1996). If and when these areas develop and their population’s incomes rise, the prospects for a vast expansion of motorization and increase in fossil fuel use and GHG emissions is very real. And these prospects are exacerbated by the evidence that the most attractive form of transport for most people as their incomes rise is the motorized personal vehicle, which is seen as a status symbol as well as being faster, flexible, convenient and more comfortable than public transport. Further aggravating the energy and environmental concerns of the expansion of motorization is the large-scale importation of used vehicles into the developing world. Although increased access to activities and services will contribute greatly to living standards, a critical goal will be to improve access while reducing the adverse consequences of motorization, including GHG emissions. Another factor that has accelerated the increase in transport energy use and carbon emissions is the gradual growth in the size, weight and power of passenger vehicles, especially in the industrialized world. Although the efficiency of vehicle technology has improved steadily over time, much of the benefit of these improvements have gone towards increased power and size at the expense of improved fuel efficiency. For example, the US Environmental Protection Agency has concluded that
6 7 8
the US new Light-duty Vehicle (LDV) fleet fuel economy in 2005 would have been 24% higher had the fleet remained at the weight and performance distribution it had in 1987. Instead, over that time period, it became 27% heavier and 30% faster in 0–60 mph (0–97 km/h) time, and achieved 5% poorer fuel economy (Heavenrich, 2005). In other words, if power and size had been held constant during this period, the fuel consumption rates of light-duty vehicles would have dropped more than 1% per year. Worldwide travel studies have shown that the average time budget for travel is roughly constant worldwide, with the relative speed of travel determining distances travelled yearly (Schafer, 2000). As incomes have risen, travellers have shifted to faster – and more energy-intensive – modes, from walking and bicycling to public transport to automobiles and, for longer trips, to aircraft. And as income and travel have risen, the percentage of trips made by automobiles has risen. Automobile travel now accounts for 15–30% of total trips in the developing world, but 50% in Western Europe and 90% in the United States. The world auto fleet has grown with exceptional rapidity – between 1950 and 1997, the fleet increased from about 50 million vehicles to 580 million vehicles, five times faster than the growth in population. In China, for example, vehicle sales (not including scooters, motorcycles and locally manufactured rural vehicles) have increased from 2.4 million in 2001 to 5.6 million in 20057 and further to 7.2 million in 2006.8 2-wheeled scooters and motorcycles have also played an important role in the developing world and in warmer parts of Europe, with a current world fleet of a few hundred million
6.21 miles/day. Automotive News Data Center: http://www.autonews.com/apps/pbcs.dll/search?Category=DATACENTER01archive. China Association of Automobile Manufacturers 2007.1.17: http://60.195.249.78/caam/caam.web/Detail.asp?id=359#
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vehicles (WBSCD, 2002). Non-motorized transport continues to dominate the developing world. Even in Latin America and Europe, walking accounts for 20–40% of all trips in many cities (WBCSD, 2002). Bicycles continue to play a major role in much of Asia and scattered cities elsewhere, including Amsterdam and Copenhagen. Public transport plays a crucial role in urban areas. Buses, though declining in importance against private cars in the industrialized world (EC, 2005; Japanese Statistical Bureau, 2006; US Bureau of Transportation Statistics, 2005) and some emerging economies, are increasing their role elsewhere, serving up to 45% of trips in some areas. Paratransit – primarily minibus jitneys run by private operators – has been rapidly taking market share from the formal public-sector bus systems in many areas, now accounting for 35% of trips in South Africa, 40% in Caracas and Bogota and up to 65% in Manila and other southeast Asian cities (WBCSD, 2002). Heavy rail transit systems are generally found only in the largest, densest cities of the industrialized world and a few of the upper-tier developing world cities. Intercity and international travel is growing rapidly, driven by growing international investments and reduced trade restrictions, increases in international migration and rising incomes that fuel a desire for increased recreational travel. In the United States, intercity travel already accounts for about one-fifth of total travel and is dominated by auto and air. European and Japanese intercity travel combines auto and air travel with fast rail travel. In the developing world, on the other hand, intercity travel is dominated by bus and conventional rail travel, though air travel is growing rapidly in some areas – 12% per year in China, for example. Worldwide passenger air travel is growing 5% annually – a faster rate of growth than any other travel mode (WBCSD, 2002). Industrialization and globalization have also stimulated freight transport, which now consumes 35% of all transport energy, or 27 exajoules (out of 77 total) (WBCSD, 2004b). Freight transport is considerably more conscious of energy efficiency considerations than passenger travel because of pressure on shippers to cut costs, however this can be offset by pressure to increase speeds and reliability and provide smaller ‘just-intime’ shipments. The result has been that, although the energyefficiency of specific modes has been increasing, there has been an ongoing movement to the faster and more energy-intensive modes. Consequently, rail and domestic waterways’ shares of total freight movement have been declining, while highway’s share has been increasing and air freight, though it remains a small share, has been growing rapidly. Some breakdowns: • Urban freight is dominated by trucks of all sizes. • Regional freight is dominated by large trucks, with bulk commodities carried by rail and pipelines and some water transport. 9
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• National or continental freight is carried by a combination of large trucks on higher speed roads, rail and ship. • International freight is dominated by ocean shipping. The bulk of international freight is carried aboard extremely large ships carrying bulk dry cargo (e.g., iron ore), container freight or fuel and chemicals (tankers). • There is considerable variation in freight transport around the world, depending on geography, available infrastructure and economic development. The United States’ freight transport system, which has the highest total traffic in the world, is one in which all modes participate substantially. Russia’s freight system, in contrast, is dominated by rail and pipelines, whereas Europe’s freight systems are dominated by trucking with a market share of 72% (tkm) in EU-25 countries, while rail’s market share is just 16.4% despite its extensive network.9 China’s freight system uses rail as its largest carrier, with substantial contributions from trucks and shipping (EC, 2005). Global estimates of direct GHG emissions of the transport sector are based on fuel use. The contribution of transport to total GHG emissions was about 23%, with emissions of CO2 and N2O amounting to about 6300–6400 MtCO2-eq in 2004. Transport sector CO2 emissions have increased by around 27% since 1990 (IEA, 2006d). For sub-sectors such as aviation and marine transport, estimates based on more detailed information are available. Estimates of global aviation CO2 emissions using a consistent inventory methodology have recently been made by Lee et al. (2005). These showed an increase by approximately a factor of 1.5 from 331 MtCO2/yr in 1990 to 480 MtCO2/yr in 2000. For seagoing shipping, fuel usage has previously been derived from energy statistics (e.g., Olivier et al., 1996; Corbett et al., 1999; Endresen et al., 2003). More recently, efforts have been committed to constructing inventories using activitybased statistics on shipping movements (Corbett and Köhler, 2003; Eyring et al., 2005a). This has resulted in a substantial discrepancy. Estimated CO2 emissions vary accordingly. This has prompted debate over inventory methodologies in the literature (Endresen et al., 2004; Corbett and Köhler, 2004). It is noteworthy that the NOx emissions estimates also vary strongly between the different studies (Eyring et al., 2005a). 5.2.2
Transport in the future
There seems little doubt that, short of worldwide economic collapse, transport activity will continue to grow at a rapid pace for the foreseeable future. However, the shape of that demand and the means by which it will be satisfied depend on several factors. First, it is not clear whether oil can continue to be the dominant feedstock of transport. There is an on-going debate about the date when conventional oil production will peak, with many arguing that this will occur within the next few decades
This rather small share is the result of priority given to passenger transport and market fragmentation between rival national rail systems.
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Box 5.1: Non-CO2 climate impacts When considering the mitigation potential for the transport sector, it is important to understand the effects that it has on climate change. Whilst the principal GHG emitted is CO2, other pollutants and effects may be important and control/ mitigation of these may have either technological or operational trade-offs. Individual sectors have not been studied in great detail, with the exception of aviation. Whilst surface vehicular transport has a large fraction of global emissions of CO2, its radiative forcing (RF) impact is little studied. Vehicle emissions of NOx, VOCs and CO contribute to the formation of tropospheric O3, a powerful GHG; moreover, black carbon and organic carbon may affect RF from this sector. Shipping has a variety of associated emissions, similar in many respects to surface vehicular transport. One of shipping’s particular features is the observed formation of low-level clouds (‘ship-tracks’), which has a negative RF effect. The potential coverage of these clouds and its associated RF is poorly studied, but one study estimates a negative forcing of 0.110 W/m2 (Capaldo et al., 1999), which is potentially much larger than its positive forcing from CO2 and it is possible that the overall forcing from shipping may be negative, although this requires more study. However, a distinction should be drawn between RF and an actual climate effect in terms of global temperature change or sea-level rise; the latter being much more complicated to estimate. Non-CO2 emissions (CH4 and N2O) from road transport in major Annex I parties are listed in UNFCC GHG inventory data. The refrigerant banks and emission trend of F-gases (CFC-12 + HFC-134a) from air-conditioning are reported in the recent IPCC special report on Safeguarding the Ozone Layer and the Global Climate System (IPCC, 2005). Since a rapid switch from CFC-12 to HFC-134a, which has a much lower GWP index, is taking place, the total amount of F-gases is increasing due to the increase in vehicles with air-conditioning, but total emission in CO2-eq is decreasing and forecasted to continue to decrease. Using the recent ADEME data (2006) on F-gas emissions, the shares of emissions from transport sectors for CO2, CH4, N2O and F-gases (CFC-12 + HFC-134a+HCFC-22) are: CO2 (%)
CH4 (%)
N2O (%)
F-gas (%)
USA
88.4
0.2
2.0
8.9
Japan
96.0
0.1
2.5
1.4
EU
95.3
0.3
2.8
1.7
Worldwide F-gas emissions in 2003 were reported to be 610 MtCO2-eq in IPCC (2005), but more recent ADEME data (ADEME, 2006) was about 310 Mt CO2-eq (CFC-12 207, HFC-134a 89, HCFC-22 10 MtCO2-eq), which is about 5% of total transport CO2 emission. It can be seen that non-CO2 emissions from the transport sector are considerably smaller than the CO2 emissions. Also, air-conditioning uses significant quantities of energy, with consequent CO2 emissions from the fuel used to supply this energy. Although this depends strongly on the climate conditions, it is reported to be 2.5–7.5% of vehicle energy consumption (IPCC, 2005). Aviation has a larger impact on radiative forcing than that from its CO2 forcing alone. This was estimated for 1992 and a range of 2050 scenarios by IPCC (1999) and updated for 2000 by Sausen et al. (2005) using more recent scientific knowledge and data. Aviation emissions impact radiative forcing in positive (warming) and negative (cooling) ways as follows: CO2 (+25.3 mW/m2); O3 production from NOx emissions (+21.9 mW/m2); ambient CH4 reduction as a result of NOx emissions (–10.4 mW/ m2); H2O (+2.0 mW/m2); sulphate particles (–3.5 mW/m/2); soot particles (+2.5 mW/m2); contrails (+10.0 mW/m2); cirrus cloud enhancement (10–80 mW/m2). These effects result in a total aviation radiative forcing for 2000 of 47.8 mW/m2, excluding cirrus cloud enhancement, for which no best estimate could be made, as was the case for IPCC (1999). Forster et al. (2007) assumed that aviation radiative forcing (0.048 W/m2 in 2000, which excludes cirrus) to have grown by no more that 10% between 2000 and 2005. Forster et al. (2007) estimate a total net anthropogenic radiative forcing in 2005 of 1.6 W/m2 (range 0.6–2.4 W/m2). Aviation therefore accounts for around 3% of the anthropogenic radiative forcing in 2005 (range 2–8%). This 90% confidence range is skewed towards lower percentages and does not account for uncertainty in the aviation forcings.
(though others, including some of the major multinational oil companies, strongly oppose this view). Transport can be fuelled by multiple alternative sources, beginning with liquid fuels from unconventional oil (very heavy oil, oil sands and oil shale), natural gas or coal, or biomass. Other alternatives include gaseous fuels such as natural gas or hydrogen and
electricity, with both hydrogen and electricity capable of being produced from a variety of feedstocks. However, all of these alternatives are costly, and several – especially liquids from fossil resources – can increase GHG emissions significantly without carbon sequestration.
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Vehicle Ownership/ 1000 Persons 900 800 USA
700 600
New Zealand
500
Australia
France
Spain
Sweden
400 Czech 300 Poland 200
UK
Canada Japan Switzerland Belgium Germany Netherlands Denmark
Portugal Greece
Hungary
Argentina Saudi Arabia Mexico KoreaAfrica Peru 100 South Brazil Turkey 0 India Philippines China 15000 0 10000 5000 Russia
Italy
Malaysia
20000
25000
30000
35000
GDP per Capita (US$) Figure 5.2: Vehicle ownership as a function of per capita income Note: plotted years vary by country depending on data availability. Data source: World Bank, 2004.
Second, the growth rate and shape of economic development, the primary driver of transport demand, is uncertain. If China and India as well as other Asian countries continue to rapidly industrialize, and if Latin America and Africa fulfil much of their economic potential, transport demand will grow with extreme rapidity over the next several decades. Even in the most conservative economic scenarios though, considerable growth in travel is likely. Third, transport technology has been evolving rapidly. The energy efficiency of the different modes, vehicle technologies, and fuels, as well as their cost and desirability, will be strongly affected by technology developments in the future. For example, although hybrid electric drive trains have made a strong early showing in the Japanese and US markets, their ultimate degree of market penetration will depend strongly on further cost reductions. Other near-term options include the migration of light-duty diesel from Europe to other regions. Longer term opportunities requiring more advanced technology include new biomass fuels beyond those made from sugar cane in Brazil and corn in the USA, fuel cells running on hydrogen and batterypowered electric vehicles. Fourth, as incomes in the developing nations grow, transport infrastructure will grow rapidly. Current trends point towards 332
growing dependence on private cars, but other alternatives exist (as demonstrated by cities such as Curitiba and Bogota with their rapid bus transit systems). Also, as seen in Figure 5.2, the intensity of car ownership varies widely around the world even when differences in income are accounted for, so different countries have made very different choices as they have developed. The future choices made by both governments and travellers will have huge implications for future transport energy demand and CO2 emissions in these countries. Most projections of transport energy consumption and GHG emissions have developed Reference Cases that try to imagine what the future would look like if governments essentially continued their existing policies without adapting to new conditions. These Reference Cases establish a baseline against which changes caused by new policies and measures can be measured, and illustrate the types of problems and issues that will face governments in the future. Two widely cited projections of world transport energy use are the Reference Cases in the ongoing world energy forecasts of the United States Energy Information Administration, ‘International Energy Outlook 2005’ (EIA, 2005) and the International Energy Agency, World Energy Outlook 2004 (IEA, 2004a). A recent study by the World Business Council on
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200
EJ Africa Latin America Middle East India
150 Rail
Water
Other Asia
Air
China Eastern Europe EECCA OECD Pacific
100 Buses Freight trucks
OECD Europe
50
2-3 wheelers OECD N. America
LDVs 0 2000
Bunker fuel
2010
2020
2030
2040
2050
2000 2010
2020
2030
2040
2050
Figure 5.3: Projection of transport energy consumption by region and mode Source: WBCSD, 2004a.
Sustainable Development, ‘Mobility 2030’, also developed a projection of world transport energy use. Because the WBCSD forecast was undertaken by IEA personnel (WBCSD, 2004b), the WEO 2004 and Mobility 2030 forecasts are quite similar. The WEO 2006 (IEA, 2006b) includes higher oil price assumptions than previously. Its projections therefore tend to be somewhat lower than the two other studies. The three forecasts all assume that world oil supplies will be sufficient to accommodate the large projected increases in oil demand, and that world economies continue to grow without significant disruptions. With this caveat, all three forecast robust growth in world transport energy use over the next few decades, at a rate of around 2% per year. This means that transport energy use in 2030 will be about 80% higher than in 2002 (see Figure 5.3). Almost all of this new consumption is expected to be in petroleum fuels, which the forecasts project will remain between 93% and slightly over 95% of transport fuel use over the period. As a result, CO2 emissions will essentially grow in lockstep with energy consumption (see Figure 5.4). Another important conclusion is that there will be a significant regional shift in transport energy consumption, with the emerging economies gaining significantly in share (Figure 5.3). EIA’s International Energy Outlook 2005, as well as the IEA, projects a robust 3.6% per year growth rate for these economies, while the IEA’s more recent WEO 2006 projects transport demand growth of 3.2%. In China, the number of cars has been growing at a rate of 20% per year, and personal travel has increased by a factor of five over the past 20 years. At its projected 6% rate of growth, China’s transport energy use would nearly quadruple between 2002 and 2025, from 4.3 EJ in 2002 to 16.4 EJ in 2025. China’s neighbour India’s transport energy is projected to grow at 4.7% per year during this period and countries such as Thailand, Indonesia, Malaysia and Singapore
will see growth rates above 3% per year. Similarly, the Middle East, Africa and Central and South America will see transport energy growth rates at or near 3% per year. The net effect is that the emerging economies’ share of world transport energy use would grow in the EIA forecasts from 31% in 2002 to 43% in 2025. In 2004, the transport sector produced 6.2 GtCO2 emissions (23% of world energy-related CO2 emissions). The share of Non-OECD countries is 36% now and will increase rapidly to 46% by 2030 if current trends continue. In contrast, transport energy use in the mature market economies is projected to grow more slowly. EIA forecasts 1.2% per year and IEA forecasts 1.3% per year for the OECD nations. EIA projects transport energy in the United States to grow at 1.7% per year, with moderate population and travel growth and only modest improvement in efficiency. Western Europe’s transport energy is projected to grow at a much slower 0.4% per year, because of slower population growth, high fuel taxes and significant improvements in efficiency. IEA projects a considerably higher 1.4% per year for OECD Europe. Japan, with an aging population, high taxes and low birth rates, is projected to grow at only 0.2% per year. These rates would lead to 2002–2025 increases of 46%, 10% and 5%, for the USA, Western Europe and Japan, respectively. These economies’ share of world transport energy would decline from 62% in 2002 to 51% in 2025. The sectors propelling worldwide transport energy growth are primarily light-duty vehicles, freight trucks and air travel. The Mobility 2030 study projects that these three sectors will be responsible for 38, 27 and 23%, respectively, of the total 100 EJ growth in transport energy that it foresees in the 2000–2050 period. The WBCSD/SMP reference case projection indicates that the number of LDVs will grow to about 1.3 billion by 2030 and to just over 2 billion by 2050, which is almost three times 333
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15
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Gt CO2
historical data (IEA)
Syndrome) during this period, and is currently growing at 5.9% per year. These figures disguise regional differences in growth rate: for example, Europe-Asia/Pacific traffic grew at 12.2% and North American domestic traffic grew at 2.6% per year in 2005. ICAO’s outlook for the future forecasts a passenger traffic demand growth of 4.3% per year to 2020. Industry forecasts offer similar prospects for growth: the Airbus Global Market Forecast (Airbus, 2004) and Boeing Current Market Outlook (Boeing, 2006) suggest passenger traffic growth trends of 5.3% and 4.9% respectively, and freight trends at 5.9% and 6.1% respectively over the next 20 or 25 years. In summary, these forecasts and others predict a global average annual passenger traffic growth of around 5% – passenger traffic doubling in 15 years – with freight traffic growing at a faster rate that passenger traffic, although from a smaller base.
estimated data (WBCSD)
10 Air Sea 5
Road 0 1970
1980
2000
1990
2010
2020
2030
2040
2050
Figure 5.4: Historical and projected CO2 emission from transport by modes, 1970–2050 Source: IEA, 2005; WBCSD, 2004b.
higher than the present level (Figure 5.5). Nearly all of this increase will be in the developing world. Aviation Civil aviation is one of the world’s fastest growing transport means. ICAO (2006) analysis shows that aviation scheduled traffic (revenue passenger-km, RPK) has grown at an average annual rate of 3.8% between 2001 and 2005 despite the downturn from the terrorist attacks and SARS (Severe Acute Respiratory
The primary energy source for civil aviation is kerosene. Trends in energy use from aviation growth have been modelled using the Aero2K model, using unconstrained demand growth forecasts from Airbus and UK Department of Trade and Industry. The model results suggest that by 2025 traffic will increase by a factor of 2.6 from 2002, resulting in global aviation fuel consumption increasing by a factor of 2.1 (QinetiQ, 2004). Aero2k model results suggest that aviation emissions were approximately 492 MtCO2 and 2.06 MtNOx in 2002 and will increase to 1029 and 3.31 Mt respectively by 2025. Several organizations have constructed scenarios of aviation emissions to 2050 (Figure 5.6), including: • IPCC (1999) under various technology and GDP assumptions (IS92a, e and c). Emissions were most strongly affected by
Billions 2.5
x3 2.0
Africa
1.5
Latin America Middle East India
x2
Other Asia China
1.0
Eastern Europe EECCA OECD Pacific OECD Europe
0.5
OECD N. America
0 2000
2010
Figure 5.5: Total stock of light-duty vehicles by region Source: WBCSD, 2004a.
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2020
2030
2040
2050
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3000
Mt CO2/yr
FAST-A1
2500
2,442 2,377 2,302
FAST-B2 CONSAVE ULS CONSAVE RPP
2000
CONSAVE FW 1,727
1500 1,262
1,654 1,597 1,440
1,306
584
480
500
359 331
492
783 739 735
IPCCFe1 IPCCFc1 IPCCFa1
1,041
1000
CONSAVE DtE
955
907 860 749 625
800 719
ANCAT/EC2 NASA 1992 NASA 1999 AERO2K
482
404
NASA 2015 ANCAT/EC2 2015
0 1990
2000
2010
2020
2030
2040
2050
Figure 5.6: Comparison of global CO2 emissions of civil aviation, 1990–2050
the GDP assumptions, with technology assumptions having only a second order effect; • CONSAVE 2050, a European project has produced further 2050 scenarios (Berghof et al., 2005). Three of the four CONSAVE scenarios are claimed to be broadly consistent with IPCC SRES scenarios A1, A2 and B1. The results were not greatly different from those of IPCC (1999); • Owen and Lee (2005) projected aviation emissions for years 2005 through to 2020 by using ICAO-FESG forecast statistics of RPK (FESG, 2003) and a scenario methodology applied thereafter according to A1 and B2 GDP assumptions similarly to IPCC (1999). The three estimates of civil aviation CO2 emissions in 2050 from IPCC (1999) show an increase by factors of 2.3, 4.0 and 6.4 over 1992; CONSAVE (Berghof et al., 2005) four scenarios indicate increases of factors of 1.5, 1.9, 3.4 and 5.0 over 2002 emissions (QinetiQ, 2004); and FAST A1 and B2 results (Owen and Lee, 2006) indicate increases by factors of 3.3 and 5.0 over 2000 emissions. Shipping Around 90% of global merchandise is transported by sea. For many countries sea transport represents the most important mode of transport for trade. For example, for Brazil, Chile and Peru over 95% of exports in volume terms (nearly 75% in value terms) are seaborne. Economic growth and the increased integration in the world economy of countries from far-east and southeast Asia is contributing to the increase of international marine transport. Developments in China are now considered to be one of the most important stimulus to growth for the tanker, chemical, bulk and container trades (OECD, 2004b).
World seaborne trade in ton-miles recorded another consecutive annual increase in 2005, after growing by 5.1%. Crude oil and oil products dominate the demand for shipping services in terms of ton-miles (40% in 2005) (UN, 2006), indicating that demand growth will continue in the future. During 2005, the world merchant fleet expanded by 7.2%. The fleets of oil tankers and dry bulk carriers, which together make up 72.9% of the total world fleet, increased by 5.4%. There was a 13.3% increase in the container ship fleet, whose share of total fleet is 12%. Eyring et al. (2005a) provided a set of carbon emission projections out to 2050 (Eyring et al., 2005b) based upon four traffic demand scenarios corresponding to SRES A1, A2, B1, B2 (GDP) and four technology scenarios which are summarized below in Table 5.2. The resultant range of potential emissions is shown in Figure 5.7.
5.3 Mitigation technologies and strategies Many technologies and strategies are at hand to reduce the growth or even, eventually, reverse transport GHG emissions. Most of the technology options discussed here were mentioned in the TAR. The most promising strategy for the near term is incremental improvements in current vehicle technologies. Advanced technologies that provide great promise include greater use of electric-drive technologies, including hybrid335
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Table 5.2: Summary of shipping technology scenarios Technology scenario 1 (TS1) – ‘Clean scenario’
Technology scenario 2 (TS2) – ‘Medium scenario’
Technology scenario 3 (TS3) – ‘IMO compliant scenario’
Technology scenario 4 (TS4) – ‘BAU’
Low S content fuel (1%/0.5%), aggressive NOx reductions
Relatively low S content fuel (1.8%/1.2%), moderate NOx reduction
High S content fuel (2%/2%), NOx reductions according to IMO stringency only
High S content fuel (2%/2%), NOx reductions according to IMO stringency only
Fleet = 75% diesel, 25% alternative plant
Fleet = 75% diesel, 25% alternative plant
Fleet = 75% diesel, 25% alternative plant
Fleet = 100% diesel
Note: The fuel S percentages refer to values assumed in (2020/2050). Source: Eyring et al. 2005b.
electric power trains, fuel cells and battery electric vehicles. The use of alternative fuels such as natural gas, biofuels, electricity and hydrogen, in combination with improved conventional and advanced technologies; provide the potential for even larger reductions. Even with all these improved technologies and fuels, it is expected that petroleum will retain its dominant share of transport energy use and that transport GHG emissions will continue to increase into the foreseeable future. Only with sharp changes in economic growth, major behavioural shifts, and/or major policy intervention would transport GHG emissions decrease substantially. 5.3.1
Road transport
GHG emissions associated with vehicles can be reduced by four types of measures: 1. Reducing the loads (weight, rolling and air resistance and accessory loads) on the vehicle, thus reducing the work needed to operate it; 2. Increasing the efficiency of converting the fuel energy to work, by improving drive train efficiency and recapturing energy losses;
3. Changing to a less carbon-intensive fuel; and 4. Reducing emissions of non-CO2 GHGs from vehicle exhaust and climate controls. The loads on the vehicle consist of the force needed to accelerate the vehicle, to overcome inertia; vehicle weight when climbing slopes; the rolling resistance of the tyres; aerodynamic forces; and accessory loads. In urban stop-and-go driving, aerodynamic forces play little role, but rolling resistance and especially inertial forces are critical. In steady highway driving, aerodynamic forces dominate, because these forces increase with the square of velocity; aerodynamic forces at 90 km/h10 are four times the forces at 45 km/h. Reducing inertial loads is accomplished by reducing vehicle weight, with improved design and greater use of lightweight materials. Reducing tyre losses is accomplished by improving tyre design and materials, to reduce the tyres’ rolling resistance coefficient, as well as by maintaining proper tyre pressure; weight reduction also contributes, because tyre losses are a linear function of vehicle weight. And reducing aerodynamic forces is accomplished by changing the shape of the vehicle, smoothing vehicle surfaces, reducing the vehicle’s cross-section, controlling airflow under the vehicle and other measures. Measures to reduce the heating and cooling needs of the passengers, for example by changing window glass to reflect incoming solar radiation, are included in the group of measures.
Mt C 600 D1TS1 D1TS2 D1TS3 D1TS4 D2TS1 D2TS2 D2TS3 D2TS4 D3TS1 D3TS2 D3TS3 D3TS4 D4TS1 D4TS2 D4TS3 D4TS4
500 400 300 200 100 0 1950
1970
1990
2010
2030
2050
Figure 5.7: Historical and projected CO2 emissions of seagoing shipping, 19902050 Note: See Table 5.2 for the explanation of the scenarios. Source: adapted from Eyring et al., 2005a,b.
10 1 km/h = 0.621 mph
336
Increasing the efficiency with which the chemical energy in the fuel is transformed into work, to move the vehicle and provide comfort and other services to passengers, will also reduce GHG emissions. This includes measures to improve engine efficiency and the efficiency of the rest of the drive train and accessories, including air conditioning and heating. The range of measures here is quite great; for example, engine efficiency can be improved by three different kinds of measures, increasing thermodynamic efficiency, reducing frictional losses and reducing pumping losses (these losses are the energy needed to pump air and fuel into the cylinders and push out the exhaust) and each kind of measure can be addressed by a great number of design, material and technology changes. Improvements in transmissions can reduce losses in the transmission itself and help engines to operate in their most
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Transport and its infrastructure
efficient modes. Also, some of the energy used to overcome inertia and accelerate the vehicle – normally lost when the vehicle is slowed, to aerodynamic forces and rolling resistance as well to the mechanical brakes (as heat) – may be recaptured as electrical energy if regenerative braking is available (see the discussion of hybrid electric drive trains). The use of different liquid fuels, in blends with gasoline and diesel or as ‘neat fuels’ require minimal or no changes to the vehicle, while a variety of gaseous fuels and electricity would require major changes. Alternative liquid fuels include ethanol, biodiesel and methanol, and synthetic gasoline and diesel made from natural gas, coal, or other feedstocks. Gaseous fuels include natural gas, propane, dimethyl ether (a diesel substitute) and hydrogen. Each fuel can be made from multiple sources, with a wide range of GHG emission consequences. In evaluating the effects of different fuels on GHG emissions, it is crucial to consider GHG emissions associated with fuel production and distribution in addition to vehicle tailpipe emissions (see the section on well-to-wheels analysis). For example, the consumption of hydrogen produces no emissions aside from water directly from the vehicle, but GHG emissions from hydrogen production can be quite high if the hydrogen is produced from fossil fuels (unless the carbon dioxide from the hydrogen production is sequestered). The sections that follow discuss a number of technology, design and fuel measures to reduce GHG emissions from vehicles. 5.3.1.1
Reducing vehicle loads
Lightweight materials A 10% weight reduction from a total vehicle weight can improve fuel economy by 4–8%, depending on changes in vehicle size and whether or not the engine is downsized. There are several ways to reduce vehicle weight; including switching to high strength steels (HSS), replacing steel by lighter materials such as Al, Mg and plastics, evolution of lighter design concepts and forming technologies. The amount of lighter materials in vehicles has been progressively increasing over time, although not always resulting in weight reductions and better fuel economy if they are used to increase the size or performance of the vehicle. In fact, the average weight of a vehicle in the USA and Japan has increased by 10–20% in the last 10 years (JAMA, 2002; Haight, 2003), partly due to increased concern for safety and customers’ desire for greater comfort. Steel is still the main material used in vehicles, currently averaging 70% of kerb weight. Aluminium usage has grown to roughly 100 kg per average passenger car, mainly in the engine, drive train and chassis in the form of castings and forgings. Aluminium is twice as strong as an equal weight of
steel, allowing the designer to provide strong, yet lightweight structures. Aluminium use in body structures is limited, but there are a few commercial vehicles with all Al bodies (e.g., Audi’s A2 and A8). Where more than 200 kg of Al is used and secondary weight reductions are gained by down-sizing the engine and suspension – more than 11–13% weight reduction can be achieved. Ford’s P2000 concept car11 has demonstrated that up to 300 kg of Al can be used in a 900 kg vehicle. Magnesium has a density of 1.7–1.8 g/cc12, about 1/4 that of steel, while attaining a similar (volumetric) strength. Major hurdles for automobile application of magnesium are its high cost and performances issues such as low creep strength and contact corrosion susceptibility. At present, the use of magnesium in vehicle is limited to only 0.1–0.3% of the whole weight. However, its usage in North American-built family vehicles has been expanding by 10 to 14% annually in recent years. Aluminium has grown at 4–6%; plastics by 1–1.8%; and high strength steels by 3.5–4%. Since the amount of energy required to produce Mg and also Al is large compared with steel, LCA analysis is important in evaluating these materials’ potential for CO2 emission reduction (Helms and Lambrecht, 2006). Also, the extent of recycling is an important issue for these metals. The use of plastics in vehicles has increased to about 8% of total vehicle weight, which corresponds to 100-120 kg per vehicle. The growth rate of plastics content has been decreasing in recent years however, probably due to concerns about recycling, given that most of the plastic goes to the automobile shredder residue (ASR) at the end of vehicle life. Fibrereinforced plastic (FRP) is now widely used in aviation, but its application to automobiles is limited due to its high cost and long processing time. However, its weight reduction potential is very high, maybe as much as 60%. Examples of FRP structures manufactured using RTM (resin transfer method) technology are wheel housings or entire floor assemblies. For a compactsize car, this would make it possible to reduce the weight; of a floor assembly (including wheel housings) by 60%, or 22 kg per car compared to a steel floor assembly. Research examples of plastics use in the chassis are leaf or coil springs manufactured from fibre composite plastic. Weight reduction potentials of up to 63% have been achieved in demonstrators using glass and/or carbon fibre structures (Friedricht, 2002). Aside from the effect of the growing use of non-steel materials, the reduction in the average weight of steel in a car is driven by the growing shift from conventional steels to high strength steels (HSS). There are various types of HSS, from relatively low strength grade (around 400 MPa) such as solution-hardened and precipitation-hardened HSS to very high strength grade (980–1400 MPa) such as TRIP steel and tempered martensitic HSS. At present, the average usage per vehicle of HSS is 160 kg (11% of whole weight) in the USA
11 SAE International (Society of Automotive Engineers): The aluminum angle, automotive engineering on-line, http://www.sae.org/automag/metals/10.htm. 12 Specific gravity 1738
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and 75 kg (7%) in Japan. In the latest Mercedes A-class vehicle, HSS comprises 67% of body structure weight. The international ULSAB-AVC project (Ultra Light Steel Auto Body – Advanced Vehicle Concept) investigated intensive use of HSS, including advanced HSS, and demonstrated that using HSS as much as possible can reduce vehicle weight by 214 kg (–19%) and 472 kg (–32%) for small and medium passenger cars respectively. In this concept, the total usage of HSS in body and closures structures is 280–330 kg, of which over 80% is advanced HSS (Nippon Steel, 2002). Since heavy-duty vehicles such as articulated trucks are much heavier than passenger vehicles, their weight reduction potential is much larger. It is possible to reduce the weight of tractor and trailer combination by more than 3000 kg by replacing steel with aluminium (EAA, 2001). Aerodynamics improvement Improvements have been made in the aerodynamic performance of vehicles over the past decade, but substantial additional improvements are possible. Improvement in aerodynamic performance offers important gains for vehicles operating at higher speeds, e.g., long-distance trucks and lightduty vehicles operating outside congested urban areas. For example a 10% reduction in the coefficient of drag (CD) of a medium sized passenger car would yield only about a 1% reduction in average vehicle forces on the US city cycle (with 31.4 km/h average speed), whereas the same drag reduction on the US highway cycle, with average speed of 77.2 km/h, would yield about a 4% reduction in average forces.13 These reductions in vehicle forces translate reasonably well into similar reductions in fuel consumption for most vehicles, but variations in engine efficiency with vehicle force may negate some of the benefit from drag reduction unless engine power and gearing are adjusted to take full advantage of the reduction. For light-duty vehicles, styling and functional requirements (especially for light-duty trucks) may limit the scope of improvement. However, some vehicles introduced within the past five years demonstrate that improvement potential still remains for the fleet. The Lexus 430, a conservatively styled sedan, attains a CD (coefficient of aerodynamic drag) of 0.26 versus a fleet average of over 0.3 for the US passenger car fleet. Other fleet-leading examples are: • Toyota Prius, Mercedes E-class sedans, 0.26 • Volkswagen Passat, Mercedes C240, BMW 320i, 0.27 For light trucks, General Motors’ 2005 truck fleet has reduced average CD by 5–7% by sealing unnecessary holes in the front of the vehicles, lowering their air dams, smoothing their undersides and so forth (SAE International, 2004).
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The current generation of heavy-duty trucks in the United States has average CDs ranging from 0.55 for tractor-trailers to 0.65 for tractor-tandem trailers. These trucks generally have spoilers at the top of their cabs to reduce air drag, but substantial further improvements are available. CD reductions of about 0.15, or 25% or so (worth about 12% reduced fuel consumption at a steady 65 mph14), can be obtained with a package of base flaps (simple flat plates mounted on the edges of the back end of a trailer) and side skirts (McCallen et al., 2004). The US Department of Energy’s 2012 research goals for heavy-duty trucks (USDOE, 2000)15 include a 20% reduction (from a 2002 baseline, with CD of 0.625) in aerodynamic drag for a ‘class 8’ tractor-trailer combination.16 CD reductions of 50% and higher, coupled with potential benefits in safety (from better braking and roll and stability control), may be possible with pneumatic (air blowing) devices (Englar, 2001). A complete package of aerodynamic improvements for a heavy-duty truck, including pneumatic blowing, might save about 15–20% of fuel for trucks operating primarily on uncongested highways, at a cost of about 5000 US$ in the near-term, with substantial cost reductions possible over time (Vyas et al., 2002). The importance of aerodynamic forces at higher speeds implies that reduction of vehicle highway cruising speeds can save fuel and some nations have used speed limits as fuel conservation measures, e.g., the US during the period following the 1973 oil embargo. US tests on nine vehicles with model years from 1988 to 1997 demonstrated an average 17.1% fuel economy loss in driving at 70 mph compared to 55 mph (ORNL, 2006). Recent tests on six contemporary vehicles, including two hybrids, showed similar results – the average fuel economy loss was 26.5% in driving at 80 mph compared to 60 mph, and 27.2% in driving at 70 mph compared to 50 mph (Duoba et al., 2005). Mobil Air Conditioning (MAC) systems MAC systems contribute to GHG emissions in two ways by direct emissions from leakage of refrigerant and indirect emissions from fuel consumption. Since 1990 significant progress has been made in limiting refrigerant emissions due to the implementation of the Montreal Protocol. The rapid switch from CFC-12 (GWP 8100) to HFC-134a (GWP 1300) has led to the decrease in the CO2-eq emissions from about 850 MtCO2eq in 1990 to 609 MtCO2-eq in 2003, despite the continued growth of the MAC system fleet (IPCC, 2005). Refrigerant emissions can be decreased by using new refrigerants with a much lower GWP, such as HFC-152a or CO2, restricting refrigerant sales to certified service professionals and better servicing and disposal practices. Although the feasibility of CO2 refrigerant has been demonstrated, a number of technical hurdles have still to be overcome.
The precise value would depend on the value of the initial CD as well as other aspects of the car’s design. 1 mph = 1.6 km/h Http://www.eere.energy.gov/vehiclesandfuels/about/partnerships/21centurytruck/21ct_goals.shtml. These are heavy-duty highway trucks with separate trailers, but less than 5 axles – the standard long-haul truck in the U.S.
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Since the energy consumption for MAC is estimated to be 2.5–7.5% of total vehicle energy consumption, a number of solutions have to be developed in order to limit the energy consumption of MAC, such as improvements of the design of MAC systems, including the control system and airflow management. 5.3.1.2
Improving drive train efficiency
Advanced Direct Injection Gasoline / Diesel Engines and transmissions. New engine and transmission technologies have entered the light-duty vehicle fleets of Europe, the USA and Japan, and could yield substantial reductions in carbon emissions if more widely used. Direct injection diesel engines yielding about 35% greater fuel economy than conventional gasoline engines are being used in about half the light-duty vehicles being sold in European markets, but are little used in Japan and the USA (European taxes on diesel fuel generally are substantially lower than on gasoline, which boosts diesel share). Euro 4 emission standards were enforced in 2005, with Euro 5 (still undefined) to follow around 2009–2010. These standards, plus Tier 2 standards in the USA, will challenge diesel NOx controls, adding cost and possibly reducing fuel efficiency somewhat. Euro 4/Tier 2 compliant diesels for light-duty vehicles, obtaining 30% better fuel efficiency than conventional gasoline engines, may cost about 2000–3000 US$ more than gasoline engines (EEA, 2003). Improvements to gasoline engines include direct injection. Mercedes’ M271 turbocharged direct injection engine is estimated to attain 18% reduced fuel consumption, part of which is due to intake valve control and other engine technologies (SAE International, 2003a); cylinder shutoff during low load conditions (Honda Odyssey V6, Chrysler Hemi, GM V8s) (SAE International, 2003a) and improved valve timing and lift controls. Transmissions are also being substantially improved. Mercedes, GM, Ford, Chrysler, Volkswagen and Audi are introducing advanced 6 and 7 speed automatics in their luxury vehicles, with strong estimated fuel economy improvements ranging from 4–8% over a 4-speed automatic for the Ford/GM 6speed to a claimed 13% over a manual, plus faster acceleration, for the VW/Audi BorgWarner 6-speed (SAE International, 2003b). If they follow the traditional path for such technology, these transmissions will eventually be rolled into the fleet. Also, continuously variable transmissions (CVTs), which previously had been limited to low power drive trains, are gradually rising in their power-handling capabilities and are moving into large vehicles.
The best diesel engines currently used in heavy-duty trucks are very efficient, achieving peak efficiencies in the 45–46% range (USDOE, 2000). Although recent advances in engine and drive train technology for heavy-duty trucks have focused on emissions reductions, current research programmes in the US Department of Energy are aiming at 10–20% improvements in engine efficiency within ten years (USDOE, 2000), with further improvements of up to 25% foreseen if significant departures from the traditional diesel engine platform can be achieved. Engines and drive trains can also be made more efficient by turning off the engine while idling and drawing energy from other sources. The potential for reducing idling emissions in heavy-duty trucks is significant. In the USA, a nationwide survey found that, on average, a long-haul truck consumed about 1,600 gallons, or 6,100 litres, per year from idling during driver rest periods. A variety of behavioural and technological practices could be pursued to save fuel. A technological fix is to switch to grid connections or use onboard auxiliary power units during idling (Lutsey et al., 2004). Despite the continued tightening of emissions standards for both light-duty vehicles and freight trucks, there are remaining concerns about the gap between tested emissions and onroad emissions, particularly for diesel engines. Current EU emissions testing uses test cycles that are considerably gentler than seen in actual driving, allowing manufacturers to design drive trains so that they pass emissions tests but ‘achieve better fuel efficiency or other performance enhancement at the cost of higher emissions during operation on the road (ECMT, 2006).’ Other concerns involve excessive threshold limits demanded of onboard diagnostics systems, aftermarket mechanical changes (replacement of computer chips, disconnection of exhaust gas recirculation systems) and failure to maintain required fluid levels in Selective Catalytic Reduction systems (ECMT, 2006). Similar concerns in the USA led to the phase-in between 2000 and 2004 of a more aggressive driving cycle (the US06 cycle) to emission tests for LDVs; however, the emission limits tied to this cycle were not updated when new Tier 2 emission standards were promulgated, so concerns about onroad emissions, especially for diesels, will apply to the USA as well. Hybrid drive trains Hybrid-electric drive trains combine a fuel-driven power source, such as a conventional internal combustion engine (ICE) with an electric drive train – electric motor/generator and battery (or ultracapacitor) - in various combinations.17 In current hybrids, the battery is recharged only by regenerative braking and engine charging, without external charging from the grid. ‘Plug-in hybrids,’ which would obtain part of their energy from the electric grid, can be an option but require a larger battery and perhaps a larger motor. Hybrids save energy by:
17 A hybrid drive train could use an alternative to an electric drive train, for example a hydraulic storage and power delivery system. The U.S. Environmental Protection Agency has designed such a system.
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• Shutting the engine down when the vehicle is stopped (and possibly during braking or coasting); • Recovering braking losses by using the electric motor to brake and using the electricity generated to recharge the battery; • Using the motor to boost power during acceleration, allowing engine downsizing and improving average engine efficiency; • Using the motor instead of the engine at low load (in some configurations), eliminating engine operation during its lowest efficiency mode; • Allowing the use of a more efficient cycle than the standard Otto cycle (in some hybrids); • Shifting power steering and other accessories to (more efficient) electric operation. Since the 1998 introduction of the Toyota Prius hybrid in the Japanese market, hybrid electric drive train technology has advanced substantially, expanding its markets, developing in alternative forms that offer different combinations of costs and benefits and improving component technologies and system designs. Hybrids now range from simple belt-drive alternatorstarter systems offering perhaps 7 or 8% fuel economy benefit under US driving conditions to ‘full hybrids’ such as the Prius offering perhaps 40–50% fuel economy benefits18 (the Prius itself more than doubles the fuel economy average – on the US test – of the combined 2004 US model year compact and medium size classes, although some portion of this gain is due to additional efficiency measures). Also, hybrids may improve fuel efficiency by substantially more than this in congested urban driving conditions, so might be particularly useful for urban taxis and other vehicles making frequent stops. Hybrid sales have expanded rapidly: in the United States, sales were about 7,800 in 2000 and have risen rapidly, to 207,000 in 200519; worldwide hybrid sales were about 541,000 in 2005 (IEA Hybrid Website, 2006). Improvements made to the Prius since its introduction demonstrate how hybrid technology is developing. For example, the power density of Prius’s nickel metal hydride batteries has improved from 600 W/kg1 in 1998 to 1250 W/kg1 in 2004 - a 108% improvement. Similarly, the batteries’ specific energy has increased 37% during the same period (EEA, 2003). Higher voltage in the 2004 Prius allows higher motor power with reduced electrical losses and a new braking-by-wire system maximizes recapture of braking energy. The 1998 Prius compact sedan attained 42 mpg on the US CAFE cycle, with 0–60 mph acceleration time of 14.5 seconds; the 2004 version is larger (medium size) but attains 55 mpg and a 0–60 of 10.5 seconds. Prius-type hybrid systems will add about 4,000 US$ to the price of a medium sized sedan (EEA, 2003), but continued cost reduction and development efforts should gradually reduce costs.
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Hybridization can yield benefits in addition to directly improving fuel efficiency, including (depending on the design) enhanced performance (with reduced fuel efficiency benefits in some designs), less expensive 4-wheel drive systems, provision of electric power for off-vehicle use (e.g., GM Silverado hybrid), and ease of introducing more efficient transmissions such as automated manuals (using the motor to reduce shift shock). Hybrid drive trains’ strong benefits in congested stop-and-go travel mesh well with some heavier-duty applications, including urban buses and urban delivery vehicles. An initial generation of hybrid buses in New York City obtained about a 10% improvement in fuel economy as well as improved acceleration capacity and substantially reduced emissions (Foyt, 2005). More recently, a different design achieved a 45% fuel economy increase in NYC operation (not including summer, where the increase should be lower) (Chandler et al., 2006). Fedex has claimed a 57% fuel economy improvement for its E700 diesel hybrid delivery vehicles (Green Car Congress, 2004). Hybrid applications extend to two and three-wheelers, as well, because these often operate in crowded urban areas in stopand-go operation. Honda has developed a 50 cc hybrid scooter prototype that offers about a one-third reduction in fuel use and GHG emissions compared to similar 50 cc scooters (Honda, 2004). However, sales of two and three-wheeled vehicles in most markets are extremely price sensitive, so the extent of any potential market for hybrid technology may be quite limited. Plug-in hybrids, or PHEVs, are a merging of hybrid electric and battery electric. PHEVs get some of their energy from the electricity grid. Plug-in hybrid technology could be useful for both light-duty vehicles and for a variety of medium duty vehicles, including urban buses and delivery vehicles. Substantial market success of PHEV technology is, however, likely to depend strongly on further battery development, in particular on reducing battery cost and specific energy and increasing battery lifetimes. PHEVs’ potential to reduce oil use is clear – they can use electricity to ‘fuel’ a substantial portion of miles driven. The US Electric Power Research Institute (EPRI, 2001) estimates that 30 km hybrids (those that have the capability to operate up to 30 km solely on electricity from the battery) can substitute electricity for gasoline for approximately 30–40% of miles driven in the USA. With larger batteries and motors, the vehicles could replace even more mileage. However, their potential to reduce GHG emissions more than that achieved by current hybrids depends on their sources of electricity. For regions that rely on relatively low-carbon electricity for off-peak power, e.g., natural gas combined cycle power, GHG reductions over the PHEV’s lifecycle will be substantial; in contrast, PHEVs in areas that rely on coal-fired power could have increased lifecycle
18 Precise values are somewhat controversial because of disagreements about the fuel economy impact of other fuel-saving measures on the vehicles. 19 Based on sales data from http://electricdrive.org/index.php?tg=articles&topics=7 and J.D. Power.
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Water gas shift + separation Gasification
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Figure 5.8: Overview of conversion routes from crops to biofuels Source: Adapted from Hamelinck and Faaij, 2006.
carbon emissions. In the long-term, movement to a low-carbon electricity sector could allow PHEVs to play a major role in reducing transport sector GHG emissions. 5.3.1.3
Alternative fuels
Biofuels The term biofuels describes fuel produced from biomass. A variety of techniques can be used to convert a variety of CO2 neutral biomass feedstocks into a variety of fuels. These fuels include carbon-containing liquids such as ethanol, methanol, biodiesel, di-methyl esters (DME) and Fischer-Tropsch liquids, as well as carbon-free hydrogen. Figure 5.8 shows some main routes to produce biofuels: extraction of vegetable oils, fermentation of sugars to alcohol, gasification and chemical synthetic diesel, biodiesel and bio oil. In addition, there are more experimental processes, such as photobiological processes that produce hydrogen directly. Biofuels can be used either ‘pure’ or as a blend with other automotive fuels. There is a large interest in developing biofuel technologies, not only to reduce GHG emission but more so to decrease the enormous transport sector dependence on imported oil. There are two biofuels currently used in the world for transport purposes – ethanol and biodiesel.
Ethanol is currently made primarily by the fermentation of sugars produced by plants such as sugar cane, sugar beet and corn. Ethanol is used in large quantities in Brazil where it is made from sugar cane, in the USA where it is made from corn, but only in very small quantities elsewhere. Ethanol is blended with gasoline at concentrations of 5–10% on a volume basis in North America and Europe. In Brazil ethanol is used either in its pure form replacing gasoline, or as a blend with gasoline at a concentration of 20–25%. The production of ethanol fuelled cars in Brazil achieved 96% market share in 1985, but sharply declining shortly thereafter to near zero. Ethanol vehicle sales declined because ethanol producers shifted to sugar production and consumers lost confidence in reliable ethanol supply. A 25% blend of ethanol has continued to be used. With the subsequent introduction of flexfuel cars (see Box 5.2), ethanol fuel sales have increased. However, the sugar cane experience in Brazil will be difficult to replicate elsewhere. Land is plentiful, the sugar industry is highly efficient, the crop residues (bagasse) are abundant and easily used for process energy, and a strong integrated R&D capability has been developed in cane growing and processing. In various parts of Asia and Africa, biofuels are receiving increasing attention and there is some experience with ethanol341
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Box 5.2 Flexfuel vehicle (FFV)20 Particularly in Brazil where there is large ethanol availability as an automotive fuel there has been a substantial increase in sales of flexfuel vehicles (FFV). Flexfuel vehicle sales in Brazil represent about 81% (Nov. 2006) of the market share of light-duty vehicles. The use of FFVs facilitates the introduction of new fuels. The incremental vehicle cost is small, about 100 US$. The FFVs were developed with systems that allow the use of one or more liquid fuels, stored in the same tank. This system is applied to OTTO cycle engines and enables the vehicles to run on gasoline, ethanol or both in a mixture, according to the fuel availability. The combustion control is done through an electronic device, which identifies the fuel being used and then the engine control system makes the suitable adjustments allowing the running of the engine in the most adequate condition. One of the greatest advantages of FFVs is their flexibility to choose their fuel depending mainly on price. The disadvantage is that the engine cannot be optimized for the attributes of a single fuel, resulting in foregone efficiency and higher pollutant emissions (though the latter problem can be largely addressed with sophisticated sensors and computer controls, as it is in the USA). In the USA21, the number of FFVs is close to 6 million and some US manufacturers are planning to expand their sales. However, unlike in the Brazilian experience, ethanol has not been widely available at fuel stations (other than as a 10% blend) and thus the vehicles rarely fuel with ethanol. Their popularity in the USA is due to special fuel economy credits available to the manufacturer.
gasoline blending of up to 20%. Ethanol is being produced from sugar cane in Africa and from corn in small amounts in Asia. Biodiesel production is being considered from Jatropha (a drought resistant crop) that can be produced in most parts of Africa (Yamba and Matsika, 2004). It is estimated that with 10% ethanol-gasoline blending and 20% biodiesel-diesel blending in southern Africa, a reduction of 2.5 MtCO2 and 9.4 MtCO2 respectively per annum can be realized. Malaysian palm oil and US soybean oils are currently being used as biodiesel transport fuel in limited quantities and other oilseed crops are being considered elsewhere.
These investments are beginning to be made. In 2006 BP announced it was committing 1 billion US$ to develop new biofuels, with special emphasis on bio-butanol, a liquid that can be easily blended with gasoline. Other large energy companies were also starting to invest substantial sums in biofuels R&D in 2006, along with the US Department of Energy, to increase plant yields, develop plants that are better matched with process conversion technologies and to improve the conversion processes. The energy companies in particular are seeking biofuels other than ethanol that would be more compatible with the existing petroleum distribution system.22
For the future, the conversion of ligno-cellulosic sources into biofuels is the most attractive biomass option. Lignocellulosic sources are grasses and woody material. These include crop residues, such as wheat and rice straw, and corn stalks and leaves, as well as dedicated energy crops. Cellulosic crops are attractive because they have much higher yields per hectare than sugar and starch crops, they may be grown in areas unsuitable for grains and other food/feed crops and thus do not compete with food, and the energy use is far less, resulting in much greater GHG reductions than with corn and most food crops (IEA, 2006a).
Biodiesel is less promising in terms of cost and production potential than cellulosic fuels but is receiving increasing attention. Bioesters are produced by a chemical reaction between vegetable or animal oil and alcohol, such as ethanol or methanol. Their properties are similar to those of diesel oil, allowing blending of bioesters with diesel or the use of 100% bioesters in diesel engines, and they are all called biodiesel. Blends of 20% biodiesel with 80% petroleum diesel (B20) can generally be used in unmodified diesel engines.23
A few small experimental cellulosic conversion plants were being built in the USA in 2006 to convert crop residues (e.g., wheat straw) into ethanol, but considerably more R&D investment is needed to make these processes commercial. 20 21 22 23
Diesel fuel can also be produced through thermochemical hydrocracking of vegetable oil and animal fats. This technology has reached the demonstration stage. In Finland and Brazil24 a commercial production project is under way. The advantage of the hydrocracked biodiesel is its stability and compatibility with conventional diesel (Koyama et al., 2006).
http://www.eere.energy.gov/afdc/afv/eth_vehicles.html, http://en.wikipedia.org/wiki/Flexible-fuel_vehicle. http://www.epa.gov/smartway/growandgo/documents/factsheet-e85.htm. http://www.greencarcongress.com/2006/06/bp_and_dupont_t.html. http://www.eere.energy.gov/afdc/altfuel/biodiesel.html.
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US $/l Biodiesel
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Figure 5.9: Comparison of cost for various biofuels with those for gasoline and diesel Source: IEA, 2006b.
A large drawback of biodiesel fuels is the very high cost of feedstocks. If waste oils are used the cost can be competitive, but the quantity of waste oils is miniscule compared to transport energy consumption. If crops are used, the feedstock costs are generally far higher than for sugar, starch or cellulosic materials. These costs are unlikely to drop since they are the same highly developed crops used for foods and food processing. Indeed, if diverted to energy use, the oil feedstock costs are likely to increase still further, creating a direct conflict with food production. The least expensive oil feedstock at present is palm oil. Research is ongoing into new ways of producing oils. The promising feedstock seems to be algae, but cost and scale issues are still uncertain. For 2030 IEA (2006a) reports mitigation potentials for bioethanol between 500–1200 MtCO2, with possibly up to 100– 300 MtCO2 of that for ligno-cellulosic ethanol (or some other bio-liquid). The long-term potential for ligno-cellulosic fuels beyond 2030 is even greater. For biodiesel, it reports mitigation potential between 100–300 MtCO2. The GHG reduction potential of biofuels, especially with cellulosic materials, is very large but uncertain. IEA estimated the total mitigation potential of biofuels in the transport sector in 2050 to range from 1800 to 2300 MtCO2 at 25 US$/tCO2-
eq. based on scenarios with a respective replacement of 13 and 25% of transport energy demand by biofuels (IEA, 2006a). The reduction uncertainty is huge because of uncertainties related to costs and GHG impacts. Only in Brazil is biofuel competitive with oil at 50 US$ per barrel or less. All others cost more. As indicated in Figure 5.9, biofuel production costs are expected to drop considerably, especially with cellulosic feedstocks. But even if the processing costs are reduced, the scale issue is problematic. These facilities have large economies of scale. However, there are large diseconomies of scale in feedstock production (Sperling, 1985). The cost of transporting bulky feedstock materials to a central point increases exponentially, and it is difficult assembling large amount of contiguous land to serve single large processing facilities. Another uncertainty is the well-to-wheel reduction in GHGs by these various biofuels. The calculations are very complex because of uncertainties in how to allocate GHG emissions across the various products likely to be produced in the biorefinery facilities, how to handle the effects of alternative uses of land, and so on, and the large variations in how the crops are grown and harvested, as well as the uncertain efficiencies and design configurations of future process technologies and
24 Brasil Energy, No.397-July/August (2006), 40:“H-Bio, The Clean Diesel”.
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Ethanol from grain, US/EU
Ethanol from sugar beet, EU
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Ethanol from cellulosic feedstock, IEA
Biodiesel from rapeseed, EU
0
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-125 % Figure 5.10: Reduction of well-to-wheels GHG emissions compared to conventionally fuelled vehicles Note: bars indicate range of estimates. Source: IEA, 2004c; EUCAR/CONCAWE/JRC, 2006.
bio-engineering plant materials. Typical examples are shown in Figure 5.10. Ethanol from sugar cane, as produced in Brazil, provides significant reductions in GHG emissions compared to gasoline and diesel fuel on a ‘well-to-wheels’ basis. These large reductions result from the relatively energy efficient nature of sugar cane production, the use of bagasse (the cellulosic stalks and leaves) as process energy and the highly advanced state of Brazilian sugar farming and processing. Ongoing research over the years has improved crop yields, farming practices and process technologies. In some facilities the bagasse is being used to cogenerate electricity which is sold back to the electricity grid. In contrast, the GHG benefits of ethanol made from corn are minor (Ribeiro & Yones-Ibrahim, 2001). Lifecycle estimates range from a net loss to gains of about 30%, relative to gasoline made from conventional oil. Farrell et al. (2006) evaluates the many studies and concludes that on average the reductions are probably about 13% compared to gasoline from conventional oil. The corn-ethanol benefits are minimal because corn farming and processing are energy intensive. Biofuels might play an important role in addressing GHG emissions in the transport sector, depending on their production pathway (Figure 5.10). In the years to come, some biofuels may become economically competitive, as the result of increased biomass yields, developments of plants that are better suited 344
to energy production, improved cellulosic conversion processes and even entirely new energy crops and conversion processes. In most cases, it will require entirely new businesses and industries. The example of ethanol in Brazil is a model. The question is the extent to which this model can be replicated elsewhere with other energy crops and production processes. The biofuel potential is limited by: • The amount of available agricultural land (and in case of competing uses for that land) for traditional and dedicated energy crops; • The quantity of economically recoverable agricultural and silvicultural waste streams; • The availability of proven and cost-effective conversion technology. Another barrier to increasing the potential is that the production of biofuels on a massive scale may require deforestation and the release of soil carbon as mentioned in Chapter 8.4. Another important point on biofuels is a view from the cost-effectiveness among the sectors. When comparing the use of biofuel in the transport sector with its use in power stations, the latter is more favourable from a cost-effectiveness point of view (ECMT, 2007). Natural Gas (CNG / LNG / GTL) Natural gas, which is mainly methane (CH4), can be used directly in vehicles or converted into more compact fuels. It may be stored in compressed (CNG) or liquefied (LNG) form
Chapter 5
on the vehicle. Also, natural gas may be converted in large petrochemical plants into petroleum-like fuels (the process is known as GTL, or gas-to-liquid). The use of natural gas as a feedstock for hydrogen is described in the hydrogen section. CNG and LNG combustion characteristics are appropriate for spark ignition engines. Their high octane rating, about 120, allows a higher compression ratio than is possible using gasoline, which can increase engine efficiency. This requires that the vehicle be dedicated to CNG or LNG, however. Many current vehicles using CNG are converted from gasoline vehicles or manufactured as bifuel vehicles, with two fuel tanks. Bifuel vehicles cannot take full advantage of CNG’s high octane ratio. CNG has been popular in polluted cities because of its good emission characteristics. However, in modern vehicles with exhaust gas after-treatment devices, the non-CO2 emissions from gasoline engines are similar to CNG, and consequently CNG loses its emission advantages in term of local pollutants; however it produces less CO2. Important constraints on its use are the need for a separate refuelling infrastructure system and higher vehicle costs – because CNG is stored under high pressure in larger and heavier fuel tanks. Gas-to-liquids (GTL) processes can produce a range of liquid transport fuels using Fischer-Tropsch or other conversion technologies. The main GTL fuel produced will be synthetic sulphur-free diesel fuel, although other fuels can also be produced. GTL processes may be a major source of liquid fuels if conventional oil production cannot keep up with growing demand, but the current processes are relatively inefficient: 61–65% (EUCAR/CONCAWE/JRC, 2006) and would lead to increased GHG emissions unless the CO2 generated is sequestered.
Transport and its infrastructure
has a lower carbon intensity (15 tC/TJ) than petroleum products (18.9–20.2 tC/TJ) (IPCC, 1996). Hydrogen / Fuel Cells During the last decade, fuel cell vehicles (FCVs) have attracted growing attention and have made significant technological progress. Drivers for development of FCVs are global warming (FCVs fuelled by hydrogen have zero CO2 emission and high efficiency), air quality (zero tailpipe emissions), and energy security (hydrogen will be produced from a wide range of sources), and the potential to provide new desirable customer attributes (low noise, new designs). There are several types of FCVs; direct-drive and hybrid power train architectures fuelled by pure hydrogen, methanol and hydrocarbons (gasoline, naphtha). FCVs with liquid fuels have advantages in terms of fuel storage and infrastructure, but they need on-board fuel reformers (fuel processors), which leads to lower vehicle efficiency (30–50% loss), longer start-up time, slower response and higher cost. Because of these disadvantages and rapid progress on direct hydrogen systems, nearly all auto manufacturers are now focused on the pure hydrogen FCV. Significant technological progress has been made since TAR including: improved fuel cell durability, cold start (sub-freezing) operation, increased range of operation, and dramatically reduced costs (although FCV drive train costs remain at least an order of magnitude greater than internal combustion engine (ICE) drive train costs) (Murakami and Uchibori, 2006).
DME can be made from natural gas, but it can also be produced by gasifying biomass, coal or even waste. It can be stored in liquid form at 5–10 bar pressure at normal temperature. This pressure is considerably lower than that required to store natural gas on board vehicles (200 bar). A major advantage of DME is its high cetane rating, which means that self-ignition will be easier. The high cetane rating makes DME suitable for use in efficient diesel engines.
In addition, many demonstration projects have been initiated since TAR25. Since 2000, members of the California Fuel Cell Partnership have placed 87 light-duty FCVs and 5 FC buses in California, which have travelled over 590,000 km on California’s roads and highways. In 2002–2003, Japanese automakers began leasing FCVs in Japan and the USA, now totalling 17 vehicles. In 2004, US DOE started government/ industry partnership ‘learning demonstrations’ for testing, demonstrating and validating hydrogen fuel cell vehicles and infrastructure and vehicle/infrastructure interfaces for complete system solutions. In Europe, there are several partnerships for FCV demonstration such as CUTE (Clean Urban Transport for Europe), CEP (Clean Energy Partnership) and ECTOS (Ecological City Transport System), using more than 30 buses and 20 passenger cars.
DME is still at the experimental stage and it is still too early to say whether it will be commercially viable. During experiments, DME has been shown to produce lower emissions of hydrocarbons, nitric oxides and carbon monoxide than diesel and zero emissions of soot (Kajitani et al., 2005). There is no current developed distribution network for DME, although it has similarities to LPG and can use a similar distribution system. DME has a potential to reduce GHG emissions since it
The recent US (NRC/NAE, 2004) and EU (JRC/IPTS, 2004) analyses conclude: Although the potential of FCVs for reducing GHG emissions is very high there are currently many barriers to be overcome before that potential can be realized in a commercial market. These are: • To develop durable, safe, and environmentally desirable fuel cell systems and hydrogen storage systems and reduce the
25 See the report of JHFC, Current status of overseas FCV demonstration, http://www.jhfc.jp/j/data/data/h17/11_h17seminar_e.pdf.
345
Transport and its infrastructure
Chapter 5
ICE
Gasoline Gasoline-HV Diesel Gasoline Naphtha LPG ($7.3-8.3/GJ)
Fuel Cell Vehicles
LNG ($8.5-10.2/GJ)
LNG with CCS NG-LiqH2 Metha
($5.9-8.0/GJ)
Coal ($6.4-8.6/GJ)
Coal with CCS Coke Oven Gas Electricity
Well-to-Tank Tank-to-Wheel
($19.2-39.2/GJ)
Electricity-Nuclear
($23.8-89.1/GJ)
Electricity-Wind/PV 0
0.5
1.0
Well-to-Wheel CO2 emission (ICE gasoline=1) Figure 5.11: Well-to-wheel CO2 emission for major pathways of hydrogen with some estimates of hydrogen production cost (numbers in parentheses) Source: Toyota/Mizuho, 2004; NRC/NAE, 2004.
cost of fuel cell and storage components to be competitive with today’s ICEs; • To develop the infrastructure to provide hydrogen for the light-duty vehicle user; • To sharply reduce the costs of hydrogen production from renewable energy sources over a time frame of decades. Or to capture and store (‘sequester’) the carbon dioxide byproduct of hydrogen production from fossil fuels. Public acceptance must also be secured in order to create demand for this technology. The IEA echoes these points while also noting that deployment of large-scale hydrogen infrastructure at this point would be premature, as some of the key technical issues that are still being worked on, such as fuel cell operating conditions and hydrogen on-board storage options, may have a considerable impact on the choice of hydrogen production, distribution and refuelling (IEA, 2005). The GHG impact of FCVs depends on the hydrogen production path and the technical efficiency achieved by vehicles and H2 production technology. At the present technology level with FCV tank-to-wheel efficiency of about 50% and where hydrogen can be produced from natural gas at 60% efficiency, well-to-wheel (WTW) CO2 emissions can be reduced by 50– 60% compared to current conventional gasoline vehicles. In the future, those efficiencies will increase and the potential of WTW CO2 reduction can be increased to nearly 70%. If hydrogen is derived from water by electrolysis using electricity produced 346
using renewable energy such as solar and wind, or nuclear energy, the entire system from fuel production to end-use in the vehicle has the potential to be a truly ‘zero emissions’. The same is almost true for hydrogen derived from fossil sources where as much as 90% of the CO2 produced during hydrogen manufacture is captured and stored (see Figure 5.11). FCV costs are expected to be much higher than conventional ICE vehicles, at least in the years immediately following their introduction and H2 costs may exceed gasoline costs. Costs for both the vehicles and fuel will almost certainly fall over time with larger-scale production and the effects of learning, but the long-term costs are highly uncertain. Figure 5.11 shows both well-to-wheels emissions estimates for several FCV pathways and their competing conventional pathways, as well as cost estimates for some of the hydrogen pathways. Although fuel cells have been the primary focus of research on potential hydrogen use in the transport sector, some automakers envision hydrogen ICEs as a useful bridge technology for introducing hydrogen into the sector and have built prototype vehicles using hydrogen. Mazda has started to lease bi-fuel (hydrogen or gasoline) vehicles using rotary engines and BMW has also converted a 7-series sedan to bi-fuel operation using liquefied hydrogen (Kiesgen et al., 2006) and is going to lease them in 2007. Available research implies that a direct injected turbocharged hydrogen engine could potentially achieve efficiency greater than a DI diesel (Wimmer et al.,
Chapter 5
2005), although research and development challenges remain, including advanced sealing technology to insure against leakage with high pressure injection. Electric vehicles Fuel cell and hybrid vehicles gain their energy from chemical fuels, converting them into electricity onboard. Pure electric vehicles operating today are either powered from off-board electricity delivered through a conductive contact – usually buses with overhead wires or trains with electrified ‘third rails’ – or by electricity acquired from the grid and stored on-board in batteries. Future all-electric vehicles might use inductive charging to acquire electricity, or use ultracapacitors or flywheels in combination with batteries to store electricity on board. The electric vehicles are driven by electric motors with high efficiencies of more than 90%, but their short driving range and short battery life have limited the market penetration. Even a limited driving range of 300 km requires a large volume of batteries weighing more than 400 kg (JHFC, 2006). Although the potential of CO2 reduction strongly depends on the power mix, well-to-wheels CO2 emission can be reduced by more than 50% compared to conventional gasoline-ICE (JHFC, 2006). Vehicle electrification requires a more powerful, sophisticated and reliable energy-storage component than lead-acid batteries. These storage components will be used to start the car and also operate powerful by-wire control systems, store regenerative braking energy and to operate the powerful motor drives needed for hybrid or electric vehicles. Nickel metal hydride (NiMH) batteries currently dominate the power-assist hybrid market and Li ion batteries dominate the portable battery business. Both are being aggressively developed for broader automotive applications. The energy density has been increased to 170 Wh kg–1 and 500 Wh L–1 for small-size commercial Li ion batteries (Sanyo, 2005) and 130 Wh kg–1 and 310 Wh L–1 for large-size EV batteries (Yuasa, 2000). While NiMH has been able to maintain hybrid vehicle high-volume business, Li ion batteries are starting to capture niche market applications (e.g., the idlestop model of Toyota’s Vitz). The major hurdle left for Li ion batteries is their high cost. Ultracapacitors offer long life and high power but low energy density and high current cost. Prospects for cost reduction and energy enhancement and the possibility of coupling the capacitor with the battery are attracting the attention of energy storage developers and automotive power technologists alike. The energy density of ultracapacitors has increased to 15–20 Wh kg–1 (Power System, 2005), compared with 40–60 Wh kg–1 for Ni-MH batteries. The cost of these advanced capacitors is in the range of several 10s of dollars/Wh, about one order of magnitude higher than Li batteries.
Transport and its infrastructure
5.3.1.4
Well-to-wheels analysis of technical mitigation options
Life cycle analysis (LCA) is the most systematic and comprehensive method for the assessment of the environmental impacts of transport technologies. However, non-availability, uncertainty or variability of data limit its application. One key difficulty is deciding where to draw the boundary for the analysis; another is treating the byproducts of fuel production systems and their GHG emission credits. Also in some cases, LCA data varies strongly across regions For automobiles, the life-cycle chain can be divided into the fuel cycle (extraction of crude oil, fuel processing, fuel transport and fuel use during operation of vehicle) and vehicle cycle (material production, vehicle manufacturing and disposal at the end-of-life). For a typical internal combustion engine (ICE) vehicle, 70–90% of energy consumption and GHG emissions take place during the fuel cycle, depending on vehicle efficiency, driving mode and lifetime driving distance (Toyota, 2004). Recent studies of the Well-to-wheels CO2 emissions of conventional and alternative fuels and vehicle propulsion concepts include a GM/ANL (2005) analysis for North America, EU-CAR/CONCAWE/JRC (2006) for Europe and Toyota/Mizuho (2004) for Japan. Some results are shown in Fig. 5.12. Some of the differences, as apparent from Figure 5.12 for ICE-gasoline and ICE-D (diesel) reflect difference in the oil producing regions and regional differences in gasoline and diesel fuel requirements and processing equipment in refineries. The Well-to-wheel CO2 emissions shown in Fig. 5.12 are for three groups of vehicle/fuel combinations – ICE/fossil fuel, ICE/biofuel and FCV. The full well-to-wheels CO2 emissions depend on not only the drive train efficiency (TTW: tank-towheel) but also the emissions during the fuel processing (WTT: well-to-tank). ICE-CNG (compressed natural gas) has 15–25% lower emissions than ICE-G (Gasoline) because natural gas is a lower-carbon fuel and ICE-D (Diesel) has 16–24% lower emissions due to the high efficiency of the diesel engine. The results for hybrids vary among the analyses due to different assumptions of vehicle efficiency and different driving cycles. Although Toyota’s analysis is based on Prius, and using Japanese 10–15 driving cycle, the potential for CO2 reduction is 20–30% in general. Table 5.3 summarizes the results and provides an overview of implementation barriers. The lifecycle emissions of ICE vehicles using biofuels and fuel cell vehicles are extremely dependent on the fuel pathways. For ICE-Biofuel, the CO2 reduction potential is very large (30–90%), though world potential is limited by high production costs for several biomass pathways and land availability. The GHG reduction potential for the natural gas-sourced hydrogen FCV is moderate, but lifecycle emissions can be dramatically reduced by using CCS 347
Transport and its infrastructure
Chapter 5
CO2 Emission( ICE-gasoline=1 ) FCV
ICE 1.0 BioFuel 0.5
0 Tank-to-Wheel
-0.5
e
G
as
ol
in
US
EU
G
as
in ol
Japan
Well-to-Tank
H e-
V C
N
l
se
G
ie
D
D
ie
l se
-H
V D
ie
s
-F el
TD D
ie
se
l-D
M
E D
ie
s
-B el
TL D
ie
l se
-B
ar
D a(
h Et
)
g Su
n) ff) -o -o G G (N (N H2 H2 G G
oo (W
ha
Et
d)
LH
c)
2
le
H
(E 2
G
Figure 5.12: Comparison of three studies on Well-to-wheels CO2 emission analyses Note: See text for an explanation of the legend. All the results are normalized by the value of ICE-G (gasoline). Source: EUCAR/CONCAWE/JRC, 2006; GM/ANL, 2005; Toyota/Mizuho, 2004.
(carbon capture and storage) technology during H2 production (FCEV-H2ccs in Table 5.3). Using renewable energy such as Cneutral biomass as a feedstock or clean electricity as an energy source (FCEV-RE-H2) also will yield very low emissions. 5.3.1.5
Road transport: mode shifts
Personal motor vehicles consume much more energy and emit far more GHGs per passenger-km than other surface passenger modes. And the number of cars (and light trucks) continues to increase virtually everywhere in the world. Growth in GHG emissions can be reduced by restraining the growth in personal vehicle ownership. Such a strategy can, however, only be successful if high levels of mobility and accessibility can be provided by alternative means. In general, collective modes of transport use less energy and generate less GHGs than private cars. Walking and biking emit even less. There is important worldwide mitigation potential if public and non-motorised transport trip share loss is reversed. The challenge is to improve public transport systems in order to preserve or augment the market share of low-emitting modes. If public transport gets more passengers, it is possible to increase the frequency of departures, which in turn may attract new passengers (Akerman and Hojer, 2006). The USA is somewhat of an anomaly, though. In the USA, passenger travel by cars generates about the same GHG
26 The number of passengers using a specific form of public transport.
348
emissions as bus and air travel on a passenger-km basis (ORNL Transportation Energy Databook; ORNL, 2006). That is mostly because buses have low load factors in the USA. Thus, in the USA, a bus-based strategy or policy will not necessarily lower GHG emissions. Shifting passengers to bus is not simply a matter of filling empty seats. To attract more passengers, it is necessary to enhance transit service. That means more buses operating more frequently – which means more GHG emissions. It is even worse than that, because transit service is already offered where ridership26 demand is greatest. Adding more service means targeting less dense corridors or adding more service on an existing route. There are good reasons to promote transit use in the USA, but energy use and GHGs are not among them. Virtually everywhere else in the world, though, transit is used more intensively and therefore has a GHG advantage relative to cars. Table 5.4 shows the broad average GHG emissions from different vehicles and transport modes in a developing country context. GHG emissions per passenger-km are lowest for transit vehicles and two-wheelers. It also highlights the fact that combining alternative fuels with public transport modes can reduce emissions even further. It is difficult to generalize, though, because of substantial differences across nations and regions. The types of buses, occupancy factors, and even topography and weather can affect emissions. For example, buses in India and China tend
Chapter 5
Transport and its infrastructure
Table 5.3: Reduction of Well-to-wheels GHG emissions for various drive train/fuel combinations
ICE
Fossil fuel
Biofuel
H2
Drive train/Fuel
GHG reduction (%)
Gasoline (2010)
12-16
Barriers
Diesel
16-24
Emissions (NOx, PM)
CNG
15-25
Infrastructure, storage
G-HEV
20-52
Cost, battery
D-HEV
29-57
Cost
Ethanol-Cereal
30-65
Cost, availability (biomass, land), competition with food
Ethanol-Sugar
79-87
Biodiesel
47-78
Advanced biofuel (cellulosic ethanol)
70-95
Technology, cost, environmental impact, competition with usage of other sectors
H2-ICE
6-16
H2 storage, cost
FCEV
43-59
FCEV+H2ccs
78-86
FCEV+RE-H2
89-99
Cost, infrastructure, deregulation FCV
Technology (stack, storage), cost, durability
Source: EUCAR/CONCAWE/JRC, 2006, GM/ANL, 2005 and Toyota/Mizuho (2004).
to be more fuel-efficient than those in the industrialized world, primarily because they have considerably smaller engines and lack air conditioning (Sperling and Salon, 2002). Public transport In addition to reducing transport emissions, public transport is considered favourably from a socially sustainable point of view because it gives higher mobility to people who do not have access to car. It is also attractive from an economically sustainable perspective since public transport provides more capacity at less marginal cost. It is less expensive to provide additional capacity by expanding bus service than building new roads or bridges. The expansion of public transport in the form of large capacity buses, light rail transit and metro or suburban rail can be feasible mitigation options for the transport sector. The development of new rail services can be an effective measure for diverting car users to carbon-efficient mode while providing existing public transport users with upgraded service. However, a major hurdle is higher capital and possibly operating cost of the project. Rail is attractive and effective at generating high ridership in very dense cities. During the 1990s, less capital-intensive public transport projects such as light rail transit (LRT) were planned and constructed in Europe, North America and Japan. The LRT systems were successful in some regions, including a number of French cities where land use and transport planning is often well integrated (Hylen and Pharoah, 2002), but less so in other cities especially in the USA (Richmond, 2001; Mackett and Edwards, 1998), where more attention has been paid to this recently.
Around the world, the concept of bus rapid transit (BRT) is gaining much attention as a substitute for LRT and as an enhancement of conventional bus service. BRT is not new. Plans and studies for various BRT type alternatives have been prepared since the 1930s and a major BRT system was installed in Curitiba, Brazil in the 1970s (Levinson et al., 2002). But only since about 2000 has the successful Brazilian experience gained serious attention from cities elsewhere. BRT is ‘a mass transit system using exclusive right of way lanes that mimic the rapidity and performance of metro systems, but utilizes bus technology rather than rail vehicle technology’ (Wright, 2004). BRT systems can be seen as enhanced bus service and an intermediate mode between conventional bus service and heavy rail systems. BRT includes features such as exclusive right of way lanes, rapid boarding and alighting, free transfers between routes and preboard fare collection and fare verification, as well as enclosed stations that are safe and comfortable, clear route maps, signage and real-time information displays, modal integration at stations and terminals, clean vehicle technologies and excellence in marketing and customer service. To be most effective, BRT systems (like other transport initiatives) should be part of a comprehensive strategy that includes increasing vehicle and fuel taxes, strict land-use controls, limits and higher fees on parking, and integrating transit systems into a broader package of mobility for all types of travellers (IEA, 2002b). Most BRT systems today are being delivered in the range of 1–15 million US$/km, depending upon the capacity requirements and complexity of the project. By contrast, elevated rail systems and underground metro systems can cost from 50 million US$ 349
Transport and its infrastructure
Chapter 5
Table 5.4: GHG Emissions from vehicles and transport modes in developing countries Load factor (average occupancy)
Table 5.5: Cost and potential estimated for BRT in Bogota
CO2-eq emissions per passenger-km (full energy cycle)
O & Ma) (%)
Fuel price per barrel (US$)
Cost (US$/tCO2)
130-170
20
40
11.22
Car (gasoline)
2.5
Car (diesel)
2.5
85-120
20
60
7.60
Car (natural gas)
2.5
100-135
50
40
12.20
Car (electric)a)
2.0
30-100
50
60
15.84
Scooter (two-stroke)
1.5
60-90
Note: Assuming 20% of the urban population uses the BRT each day.
Scooter (four-stroke)
1.5
40-60
Minibus (gasoline)
12.0
50-70
a) Operation and maintenance (O & M) costs are expected to be high as the measure involves high demand for management and implementation beyond putting up the infrastructure.
Minibus (diesel)
12.0
40-60
Source: estimate based on Bogata CDM Project (footnote 27)
Bus (diesel)
40.0
20-30
Bus (natural gas)
40.0
25-35
Bus (hydrogen fuel cell)b)
40.0
15-25
75% full
20-50
Rail Transitc)
Note: All numbers in this table are estimates and approximations and are best treated as illustrative. a) Ranges are due largely to varying mixes of carbon and non-carbon energy sources (ranging from about 20–80% coal), and also the assumption that the battery electric vehicle will tend to be somewhat smaller than conventional cars. b) Hydrogen is assumed to be made from natural gas. c) Assumes heavy urban rail technology (‘Metro’) powered by electricity generated from a mix of coal, natural gas and hydropower, with high passenger use (75% of seats filled on average). Source: Sperling and Salon, 2002.
to over 200 million US$/km (Wright, 2004). BRT systems now operate in several cities throughout North America, Europe, Latin America, Australia, New Zealand and Asia. The largest and most successful systems to date are in Latin America in Bogotá, Curitiba and Mexico City (Karekezi et al., 2003). Analysing the Bogotá Clean Development Mechanism project gives an insight into the cost and potential of implementing BRT in large cities. The CDM project shows the potential of moving about 20% of the city population per day on the BRT that mainly constitutes putting up dedicated bus lanes (130 km), articulated buses (1200) and 500 other large buses operating on feeder routes. The project is supported by an integrated fare system, centralized coordinated fleet control and improved bus management27. Using the investment costs, an assumed operation and maintenance of 20–50%28 of investment costs per year, fuel costs of 40 to 60 US$ per barrel in 2030 and a discount rate of 4%, a BRT lifespan of 30 years, the cost of implementing BRT in the city of Bogotá was estimated to range from 7.6 US$/tCO2 to 15.84 US$/tCO2 depending on the price of fuel and operation and maintenance (Table 5.5). Comparing with results of Winkelman (2006), BRT cost estimates ranged from 14-66 US$/tCO2 depending on the BRT package involved
(Table 5.6). The potential for CO2 reduction for the city of Bogotá was determined to average 247,000 tCO2 per annum or 7.4 million tCO2 over a 30 year lifespan of the project. Non-motorized transport (NMT) The prospect for the reduction in CO2 emissions by switching from cars to non-motorized transport (NMT) such as walking and cycling is dependent on local conditions. In the Netherlands, where 47% of trips are made by NMT, the NMT plays a substantial role up to distances of 7.5 km and walking up to 2.5 km (Rietveld, 2001). As more than 30% of trips made in cars in Europe cover distances of less than 3 km and 50% are less than 5 km (EC, 1999), NMT can possibly reduce car use in terms of trips and, to a lesser extent, in terms of kilometres. While the trend has been away from NMT, there is considerable potential to revive interest in NMT. In the Netherlands, with strong policies and cultural commitment, the modal share of bicycle and walking for accessing trains from home is about 35 to 40% and 25% respectively (Rietveld, 2001). Walking and cycling are highly sensitive to the local built environment (ECMT, 2004a; Lee and Mouden, 2006). In Denmark, where the modal share of cycling is 18%, urban planners seek to enhance walking and cycling by shortening journey distances and providing better cycling infrastructure (Dill and Carr 2003, Page, 2005). In the UK where over 60% of people live within a 15 minute bicycle ride of a station, NMT could be increased by offering convenient, secure bicycle parking at stations and improved bicycle carriage on trains (ECMT, 2004a). Safety is an important concern. NMT users have a much higher risk per trip of being involved in an accident than those using cars, especially in developing countries where most NMT users cannot afford to own a car (Mohan and Tiwari, 1999). Safety can be improved through traffic engineering and campaigns to educate drivers. An important co-benefit of NMT,
27 http://cdm.unfccc.int/Projects/DB/DNV-CUK1159192623.07/view.html. 28 O & M costs are expected to be high as the measure involves high demand for management and implementation beyond putting up the infrastructure.
350
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gaining increasing attention in many countries, is public health (National Academies studies in the USA; Pucher, 2004). In Bogotá, in 1998, 70% of the private car trips were under 3 km. This percentage is lower today thanks to the bike and pedestrian facilities. The design of streets was so hostile to bicycle travel that by 1998 bicycle trips accounted for less than 1% of total trips. After some 250 km of new bicycle facilities were constructed by 2001 ridership had increased to 4% of total trips. In most of Africa and in much of southern Asia, bicyclists and other non-motorised and animal traction vehicles are generally tolerated on the roadways by authorities. Non-motorised goods transport is often important for intermodal goods transport. A special form of rickshaw is used in Bangladesh, the bicycle van, which has basically the same design as a rickshaw (Hook, 2003).
Transport and its infrastructure
Table 5.6: CO2 reduction potential and cost per tCO2 reduced using public transit policies in typical Latin American cities GHG reduction potential (%)
Cost per tCO2 (US$)
BRT mode share increases from 0-5%
3.9
66
BRT mode share increases from 0-10%
8.6
59
Walking share increases from 20-25%
6.9
17
Bike share increases from 0-5%
3.9
15
Bike mode share increases from 1-10%
8.4
14
25.1
30
Transport measure
Package (BRT, pedestrian upgrades, cycleways) Source: Wright and Fulton, 2005.
Mitigation potential of modal shifts for passenger transport Rapid motorization in the developing world is beginning to have a large effect on global GHG emissions. But motorization can evolve in quite different ways at very different rates. The amount of GHG emissions can be considerably reduced by offering strong public transport, integrating transit with efficient land use, enhancing walking and cycling, encouraging minicars and electric two-wheelers and providing incentives for efficient vehicles and low-GHG fuels. Few studies have analyzed the potential effect of multiple strategies in developing nations, partly because of a severe lack of reliable data and the very large differences in vehicle mix and travel patterns among varying areas. Wright and Fulton (2005) estimated that a 5% increase in BRT mode share against a 1% mode share decrease of private automobiles, taxis and walking, plus a 2% share decrease of mini-buses can reduce CO2 emissions by 4% at an estimated cost of 66 US$/tCO2 in typical Latin American cities. A 5% or 4% increase in walking or cycling mode share in the same scenario analysis can also reduce CO2 emissions by 7% or 4% at an estimated cost of 17 or 15 US$/tCO2, respectively (Table5.6). Although the assumptions of a single infrastructure unit cost and its constant impact on modal share in the analysis might be too simple, even shifting relatively small percentages of mode share to public transport or NMT can be worthwhile, because of a 1% reduction in mode share of private automobiles represents over 1 MtCO2 through the 20-year project period.
motorization and rapid population increases, with the execution of planned investments in highway infrastructure while at the same time efforts to shift to public transport falter (Zhou and Sperling, 2001). 5.3.1.6
Fuel consumption of vehicles can be reduced through changes in driving practices. Fuel-efficient driving practices, with conventional combustion vehicles, include smoother deceleration and acceleration, keeping engine revolutions low, shutting off the engine when idling, reducing maximum speeds and maintaining proper tyre pressure (IEA, 2001). Results from studies conducted in Europe and the USA suggested possible improvement of 5–20% in fuel economy from eco-driving training. The mitigation costs of CO2 by eco-driving training were mostly estimated to be negative (ECMT/IEA, 2005). Eco-driving training can be attained with formal training programmes or on-board technology aids. It applies to drivers of all types of vehicles, from minicars to heavy-duty trucks. The major challenge is how to motivate drivers to participate in the programme, and how to make drivers maintain an efficient driving style long after participating (IEA, 2001). In the Netherlands, eco-driving training is provided as part of driving school curricula (ECMT/IEA, 2005). 5.3.2
Figure 5.13 shows the GHG transport emission results, normalized to year 2000 emissions, of four scenario analyses of developing nations and cities (Sperling and Salon, 2002). For three of the four cases, the ‘high’ scenarios are ‘businessas-usual’ scenarios assuming extrapolation of observable and emerging trends with an essentially passive government presence in transport policy. The exception is Shanghai, which is growing and changing so rapidly that ‘business-as-usual’ has little meaning. In this case the high scenario assumes both rapid
Improving driving practices (eco-driving)
Rail
Railway transport is widely used in many countries. In Europe and Japan, electricity is a major energy source for rail, while diesel is a major source in North America. Coal is also still used in some developing countries. Rail’s main roles are high speed passenger transport between large (remote) cities, high density commuter transport in the city and freight transport over long distances. Railway transport competes with other transport modes, such as air, ship, trucks and private vehicles. Major 351
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Index: 2000 emissions = 1 Low scenario High scenario
5
0 Delhi
Shanghai
Chile
S. Africa
Figure 5.13: Projections for transport GHG emissions in 2020 for some cities of developing countries Notes: Components of the Low 2020 scenario: Delhi (Bose and Sperling, 2001): Completion of planned busways and rail transit, land-use planning for high density development around railway stations, network of dedicated bus lanes, promotion of bicycle use, including purchase subsidies and special lanes, promotion of car sharing, major push for more natural gas use in vehicles, economic re-straints on personal vehicles. Shanghai (Zhou and Sperling, 2001): Emphasis on rapid rail system growth, high density development at railway sta-tions, bicycle promotion with new bike lanes and parking at transit stations, auto industry focus on minicars and farm cars rather than larger vehicles, incentives for use of high tech in minicars – electric, hybrid, fuel cell drive trains, promotion of car sharing. Chile (O’Ryan et al., 2002): Overall focus on stronger use of market-based policy to insure that vehicle users pay the full costs of driving, internalizing costs of pollution and congestion, parking surcharges and restrictions, vehicle fees, and road usage fees, improvements in bus and rail systems, encouragement of minicars, with lenient usage and parking rules and strong commitment to alternative fuels, especially natural gas. By 2020, all taxis and 10% of other light and medium vehicles will use natural gas; all new buses will use hydrogen, improvements in bus and rail sys-tems. South Africa (Prozzi et al., 2002): Land-use policies towards more efficient growth patterns, strong push to improve public transport, including use of busways in dense corridors, provision of new and better buses, strong government oversight of the minibus jitney industry, incentives to moderate private car use, coal-based synfuels shifts to imported natural gas as a feedstock Source: Sperling and Salon, 2002.
R&D goals for railway transport are higher speeds, improved comfort, cost reductions, better safety and better punctuality. Many energy efficiency technologies for railways are discussed in the web site of the International Union of Railways.29 R&D programmes aimed at CO2 reduction include: Reducing aerodynamic resistance For high speed trains such as the Japanese Shinkansen, French TGV and German ICE, aerodynamic resistance dominates vehicle loads. It is important to reduce this resistance to reduce energy consumption and CO2 emissions. Aerodynamic resistance is determined by the shape of the train. Therefore, research has been carried out to find the optimum shape by using computer simulation and wind tunnel testing. The latest series 700 Shinkansen train has reduced aerodynamic resistance by 31% compared with the first generation Shinkansen.
Reducing train weight Reduction of train weight is an effective way to reduce energy consumption and CO2 emission. Aluminium car bodies, lightweight bogies and lighter propulsion equipments are proven weight reduction measures. Regenerative braking Regenerative brakes have been used in railways for three decades, but with limited applications. For current systems, the electric energy generated by braking is used through a catenary for powering other trains, reducing energy consumption and CO2 emissions. However, regenerative braking energy cannot be effectively used when there is no train running near a braking train. Recently research in energy storage device onboard or trackside is progressing in several countries. Lithium ion batteries, ultracapacitors and flywheels are candidates for such energy storage devices. Higher efficiency propulsion system Recent research on rail propulsion has focused on superconducting on-board transformers and permanent magnet synchronous traction motors. Apart from the above technologies mainly for electric trains, there are several promising technologies for diesel swichers, including common rail injection system and hybridization/onboard use of braking energy in diesel-electric vehicles (see the web site of the International Union of Railways), 5.3.3
Fuel efficiency is a major consideration for aircraft operators as fuel currently represents around 20% of total operating costs for modern aircraft (2005 data, according to ICAO estimates30 for the scheduled airlines of Contracting States). Both aircraft and engine manufacturers pursue technological developments to reduce fuel consumption to a practical minimum. There are no fuel efficiency certification standards for civil aviation. ICAO31 has discussed the question of whether such a standard would be desirable, but has been unable to develop any form of parameter from the information available that correlates sufficiently well with the aircraft/engine performance and is therefore unable to define a fuel efficiency parameter that might be used for a standard at this time. ‘Point’ certification could drive manufacturers to comply with the regulatory requirement, possibly at the expense of fuel consumption for other operational conditions and missions. Market pressures therefore determine fuel efficiency and CO2 emissions.
29 Energy Efficiency Technologies for Railways: http://www.railway-energy.org/tfee/index.php. 30 ICAO Estimates for the scheduled airlines of Contracting States, 2005. 31 Doc. 9836, CAEP/6, 2004.
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Box 5.3 Constraints on aviation technology development Technology developments in civil aviation are brought to the marketplace only after rigorous airworthiness and safety testing. The engineering and safety standards that apply, along with exacting weight minimisation, reliability and maintainability requirements, impose constraints to technology development and diffusion that do not necessarily apply to the same degree for other transport modes. Some of these certification requirements for engines are as follows: • • • • •
Altitude relight to 30000ft – the engine must be capable of relighting under severe adverse conditions Engine starting capability between –50°C–+50°C Ice, hail and water ingestion Fan blade off test – blade to be contained and engine to run down to idle ETOPS (extended range operations) clearance – demonstrable engine reliability to allow single engine flight for up to 240 minutes for twin-engine aircraft
In addition, the need to comply with stringent engine emissions and aircraft noise standards, to offer products that allow aircraft to remain commercially viable for three decades or more and to meet the most stringent safety requirements impose significant costs for developments. Moreover, a level of engineering excellence beyond that demanded for other vehicles is the norm. It is under these exacting conditions that improvements are delivered thus affect the rate at which improvements can be offered.
Technology developments Aviation’s dependence on fossil fuels, likely to continue for the foreseeable future, drives a continuing trend of fuel efficiency improvement through aerodynamic improvements, weight reductions and engine fuel efficient developments. New technology is developed not only to be introduced into new engines, but also, where possible, to be incorporated into engines in current production. Fuel efficiency improvements also confer greater range capability and extend the operability of aircraft. Evolutionary developments of engine and airframe technology have resulted in a positive trend of fuel efficiency improvements since the passenger jet aircraft entered service, but more radical technologies are now being explored to continue this trend. Engine developments Engine developments require a balancing of the emissions produced to both satisfy operational need (fuel efficiency) and regulatory need (NOx, CO, smoke and HC). This emissions performance balance must also reflect the need to deliver safety, reliability, cost and noise performance for the industry. Developments that reduce weight, reduce aerodynamic drag or improve the operation of the aircraft can offer all-round benefits. Emissions – and noise – regulatory compliance hinders the quest for improved fuel efficiency, and is often most difficult for those engines having the highest pressure ratios (PR). Higher PRs increase the temperature of the air used for combustion in the engine, exacerbating the NOx emissions challenge. Increasing an engine’s pressure ratio is one of the options engine manufacturers use to improve engine efficiency. Higher pressure ratios are likely to be a continuing trend in engine development, possibly requiring revolutionary NOx control techniques to maintain compliance with NOx certification standards.
A further consideration is the need to balance not only emissions trade-offs, but the inevitable trade-off between emissions and noise performance from the engine and aircraft. For example, the engine may be optimised for minimum NOx emissions, at which design point the engine will burn more fuel than it might otherwise have done. A similar design compromise may reduce noise and such performance optimisation must be conducted against engine operability requirements described in Box 5.3. Aircraft developments Fuel efficiency improvements are available through improvements to the airframe, as well as the engine. Most modern civil jet aircraft have low-mounted swept wings and are powered by two or four turbofan engines mounted beneath the wings. Such subsonic aircraft are about 70% more fuel efficient per passenger-km than 40 years ago. The majority of this gain has been achieved through engine improvements and the remainder from airframe design improvements. A 20% improvement in fuel efficiency of individual aircraft types is projected by 2015 and a 40–50% improvement by 2050 relative to equivalent aircraft produced today (IPCC, 1999). The current aircraft configuration is highly evolved, but has scope for further improvement. Technological developments have to be demonstrated to offer proven benefits before they will be adopted in the aviation industry, and this coupled with the overriding safety requirements and a product lifetime that has 60% of aircraft in service at 30 years age (ICAO, 2003) results in slower change than might be seen in other transport forms. For the near term, lightweight composite materials for the majority of the aircraft structure are beginning to appear and promise significant weight reductions and fuel burn benefits. The use of composites, for example in the Boeing 787 aircraft 353
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Table 5.7: Weight breakdown for four kerosene-fuelled configurations with the same payload and range Configuration
Empty weight (t)
Payload (t)
Fuel (t)
Max TOW (t)
Baseline
236
86
178 (100%)
500
BWB
207
86
137 (77%)
430
Laminar Flying Wing (LFW)
226
86
83 (47%)
395
LFW with UDF
219
86
72 (40%)
377
Source: GbD, 2001.
(that has yet to enter service), could reduce fuel consumption by 20% below that of the aircraft the B787 will replace32. Other developments, such as the use of winglets, the use of fuselage airflow control devices and weight reductions have been studied by aircraft manufacturers and can reduce fuel consumption by around 7%33. But these can have limited practical applicability – for example, the additional fuel burn imposed by the weight of winglets can negate any fuel efficiency advantage for short haul operations. Longer term, some studies suggest that a new aircraft configuration might be necessary to realise a step change in aircraft fuel efficiency. Alternative aircraft concepts such as blended wing bodies or high aspect ratio/low sweep configuration aircraft designs might accomplish major fuel savings for some operations. The blended wing body (flying wing) is not a new concept and in theory holds the prospect of significant fuel burn reductions: estimates suggest 20–30% compared with an equivalent sized conventional aircraft carrying the same payload (GbD, 2001; Leifsson and Mason, 2005). The benefits of this tailless design result from the minimised skin friction drag, as the tail surfaces and some engine/fuselage integration can be eliminated. Its development for the future will depend on a viable market case and will incur significant design, development and production costs. Laminar flow technology (reduced airframe drag through control of the boundary layer) is likely to provide additional aerodynamic efficiency potential for the airframe, especially for long-range aircraft. This technology extends the smooth boundary layer of undisturbed airflow over more of the aerodynamic structure, in some cases requiring artificial means to promote laminar flow beyond its natural extent by suction of the disturbed flow through the aerodynamic surface. Such systems have been the subject of research work in recent times, but are still far from a flightworthy application. Long-term technical and economic viability have yet to be proven, despite studies suggesting that fuel burn could be reduced by between 10 and 20% for suitable missions (Braslow, 1999). In 2001 the Greener by Design (GbD) technology subgroup of the Royal Aeronautical Society considered a range of
32 http://www.boeing.bom/commercial/787family/specs. 33 NASA, www.nasa.gov/centers/dryden/about/Organisations/Technology/Facts?
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possible future technologies for the long-term development of the aviation industry and their possible environmental benefits (GbD, 2001). It offered a view of the fuel burn reduction benefits that some advanced concepts might offer. Concepts considered included alternative aircraft configurations such as the blended wing body and the laminar flying wing, and the use of an unducted fan (open rotor) power plant. The study concluded that these two aircraft concepts could offer significant fuel burn reduction potential compared with a conventional aircraft design carrying an equivalent payload. Other studies (Leifsson and Mason, 2005) have suggested similar results. Table 5.7 summarises, from the GbD results, the theoretical fuel savings of these future designs relative to a baseline conventional swept wing aircraft for a 12,500 km design range, with the percentage fuel burn requirements for the mission. Further reduction in both NOx and CO2 emission could be achieved by advances in airframe and propulsion systems which reduce fuel burn. In propulsion, the open rotor offers significant reductions in fuel burn over the turbofan engines used typically on current passenger jets. However, aircraft speed is reduced below typical jet aircraft speeds as a consequence of propeller tip speed limits and therefore this technology may be more suitable for short- and medium-haul operations where speed may be less important. The global average flight length in 2005 was 1239 km (ICAO, 2006) and many flights are over shorter distances than this average. However, rotor noise from such devices would need to be controlled within acceptable (regulatory) limits. In summary, airframe and engine technology developments, weight reduction through increased used of advanced structural composites, and drag reduction, particularly through the application of laminar flow control, hold the promise of further aviation fuel burn reductions over the long term. Such developments will only be accepted by the aviation industry should they offer an advantage over existing products and meet demanding safety and reliability criteria. Alternative fuels for aviation Kerosene is the primary fuel for civil aviation, but alternative fuels have been examined. These are summarised in Box 5.4.
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Transport and its infrastructure
Box 5.4 Alternative fuels for aviation The applicability of alternative and renewable fuels for civil aviation has been examined by many countries, for both the environmental benefit that might be produced and to address energy security issues. One study, The Potential for Renewable Energy Sources in Aviation (PRESAV, 2003) concluded that biodiesel, Fischer-Tropsch synthetic kerosene liquefied hydrogen (H2) could be suitable for aviation application. Fuel cost would be an issue as in comparative terms, in 2003, conventional aviation kerosene cost 4.6 US$/GJ whereas the cost of biodiesel, FT kerosene and H2 would be in the respective ranges of 33.5–52.6 US$, 8–31.7 US$, 21.5–53.8 US$/GJ. In the and elsewhere, synthetic kerosene production is being studied the engine company Pratt and Whitney noted in a presentation (Biddle, 2006) that synthetic kerosene could be ‘economically viable when crude prices reach (up to) 59 US$/barrel’. However, any alternative fuel for commercial aircraft will need to be compatible with aviation kerosene (to obviate the need for tank and system flushing on re-fuelling) and meet a comprehensive performance and safety specification.
A potential non-carbon fuel is hydrogen and there have been several studies on its use in aviation. An EC study (Airbus, 2004) developed a conceptual basis for applicability, safety, and the full environmental compatibility for a transition from kerosene to hydrogen for aviation. The study concluded that conventional aircraft designs could be modified to accommodate the larger tank sizes necessary for hydrogen fuels. However, the increased drag due to the increased fuselage volume would increase the energy consumption of the aircraft by between 9% and 14%. The weight of the aircraft structure might increase by around 23% as a result, and the maximum take-off weight would vary between +4.4% to –14.8% dependent on aircraft size, configuration and mission. The hydrogen production process would produce CO2 unless renewable energy was used and the lack of hydrogen production and delivery infrastructure would be a major obstacle. The primary environmental benefit from the use of hydrogen fuel would be the prevention of CO2 emissions during aircraft operation. But hydrogen fuelled aircraft would produce around 2.6 times more water vapour than the use of kerosene and water vapour is a GHG. The earliest implementation of this technology was suggested as between 15–20 years, provided that research work was pursued at an appropriate level. The operating cost of hydrogen-powered aircraft remains unattractive under today’s economic conditions. The introduction of biofuels could mitigate some of aviation’s carbon emissions, if biofuels can be developed to meet the demanding specifications of the aviation industry, although both the costs of such fuels and the emissions from their production process are uncertain at this time. Aviation potential practices The operational system for aviation is principally governed by air traffic management constraints. If aircraft were to operate for minimum fuel use (and CO2 emissions), the following constraints would be modified: taxi-time would be minimized; aircraft would fly at their optimum cruising altitude (for load and mission distance); aircraft would fly minimum distance between departure and destination (i.e., great circle distances) but modified to take account of prevailing winds; no holding/ stacking would be applied.
Another type of operational system/mitigation potential is to consider the total climate impact of aviation. Such studies are in their infancy but were the subject of a major European project ‘TRADE-OFF’. In this project different methods were devised to minimize the total radiative forcing impact of aviation; in practice this implies varying the cruise altitudes as O3 formation, contrails (and presumably cirrus cloud enhancement) are all sensitive to this parameter. For example, Fichter et al. (2005) found in a parametric study that contrail coverage could be reduced by approximately 45% by flying the global fleet 6,000 feet lower, but at a fuel penalty of 6% compared with a base case. Williams et al. (2003) also found that regional contrail coverage was reduced by flying lower with a penalty on fuel usage. By flying lower, NOx emissions tend to increase also, but the removal rate of NOx is more efficient at lower altitudes: this, compounded with a lower radiative efficiency of O3 at lower altitudes meant that flying lower could also imply lower O3 forcing (Grewe et al., 2002). Impacts on cirrus cloud enhancement cannot currently be modelled in the same way, since current estimates of aviation effects on cirrus are rudimentary and based upon statistical analyses of air traffic and satellite data of cloud coverage (Stordal et al., 2005) rather than modelling. However, as Fichter et al. (2005) note, to a first order, one might expect aviation-induced cirrus cloud to scale with contrails. The overall ‘trade-offs’ are complex to analyse since CO2 forcing is long lasting, being an integral over time. Moreover, the uncertainties on some aviation forcings (notably contrail and cirrus) are still high, such that the overall radiative forcing consequences of changing cruise altitudes need to be considered as a time-integrated scenario, which has not yet been done. However, if contrails prove to be worth avoiding, then such drastic action of reducing all aircraft cruising altitudes need not be done, as pointed out by Mannstein et al. (2005), since contrails can be easily avoided – in principle – by relatively small changes in flight level, due to the shallowness of ice supersaturation layers. However, this more finely tuned operational change would not necessarily apply to O3 formation as the magnitude is a continuous process rather than the case of contrails that are either short-lived or persistent. Further intensive research of the impacts is required to determine whether such operational measures can be environmentally beneficial. 355
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ATM (Air Traffic Management) environmental benefits The goal of RVSM (Reduced Vertical Separation Minimum) is to reduce the vertical separation above flight level (FL) 290 from the current 610 m (2000 ft) minimum to 305 m (1000 ft) minimum. This will allow aircraft to safely fly more optimum profiles, gain fuel savings and increase airspace capacity. The process of safely changing this separation standard requires a study to assess the actual performance of airspace users under the current separation (610 m) and potential performance under the new standard (305 m). In 1988, the ICAO Review of General Concept of Separation Panel (RGCSP) completed this study and concluded that safe implementation of the 305 m separation standard was technically feasible. A Eurocontrol study (Jelinek et al., 2002) tested the hypothesis that the implementation of RVSM would lead to reduced aviation emissions and fuel burn, since the use of RVSM offers the possibility to optimise flight profiles more readily than in the pre-existing ATC (Air Traffic Control) regime. RVSM introduces six additional flight levels between FL290 and FL410 for all States involved in the EUR RVSM programme. The study analysed the effect from three days of actual traffic just before implementation of RVSM in the European ATC region, with three traffic days immediately after implementation of RVSM. It concluded that a clear trend of increasing environmental benefit was shown. Total fuel burn, equating to CO2 and H2O emissions, was reduced by between 1.6–2.3% per year for airlines operating in the European RVSM area. This annual saving in fuel burn translates to around 310,000 tonnes annually, for the year 2003. Lower flight speeds Speed comes at a cost in terms of fuel burn, although modern jet aircraft are designed to fly at optimum speeds and altitudes to maximise the efficiencies of their design. Flying slower would be a possibility, but a different engine would be required in order to maximise the efficiencies from such operation. The propfan – this being a conventional gas turbine powering a highly efficient rotating propeller system, as an open rotor or unducted fan – is already an established technology and was developed during the late 1980s in response to a significant increase in fuel cost at the time. The scimitar shaped blades are designed to minimise aerodynamic problems associated with high blade speeds, although one problem created is the noise generated by such devices. The fuel efficiency gains from unducted fans, which essentially function as ultra high bypass ratio turbofans, are significant and require the adoption of lower aircraft speeds in order to minimise the helical mach number at the rotating blade tip. Typically the maximum cruise speed would be less than 400 miles per hour, compared with 550 mph34 for conventional jet aircraft. In the event the aero acoustic problem associated with propfans could be overcome, such aircraft might be suitable for short-haul operations where
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speed has less importance. But there would be the need to influence passenger choice: propeller driven aircraft are often perceived as old fashioned and dangerous and many passengers are reluctant to use such aircraft. 5.3.4
Shipping
In the past few years, the International Maritime Organization (IMO) has started research and discussions on the mitigation of GHG emissions by the shipping industry. The potential of technical measures to reduce CO2 emissions was estimated at 5–30% in new ships and 4–20% in old ships. These reductions could be achieved by applying current energy-saving technologies vis-à-vis hydrodynamics (hull and propeller) and machinery on new and existing ships (Marintek, 2000). The vast majority of marine propulsion and auxiliary plants onboard ocean-going ships are diesel engines. In terms of the maximum installed engine output of all civilian ships above 100 gross tonnes (GT), 96% of this energy is produced by diesel power. These engines typically have service lives of 30 years or more. It will therefore be a long time before technical measures can be implemented in the fleet on any significant scale. This implies that operational emission abatement measures on existing ships, such as speed reduction, load optimization, maintenance, fleet planning, etc., should play an important role if policy is to be effective before 2020. Marintek (2000) estimates the short-term potential of operational measures at 1–40%. These CO2 reductions could in particular be achieved by fleet optimization and routing and speed reduction. A general quantification of the potential is uncertain, because ship utilization varies across different segments of shipping and the operational aspects of shipping are not well defined. The long-term reduction potential, assuming implementation of technical or operational measures, was estimated for the major fuel consuming segments35 of the world fleet as specific case studies. The result of this analysis was that the estimated CO2 emission reduction potential of the world fleet would be 17.6% in 2010 and 28.2% in 2020. Even though this potential is significant, it was noted that this would not be sufficient to compensate for the effects of projected fleet growth (Marintek, 2000). Speed reduction was found to offer the greatest potential for reduction, followed by implementation of new and improved technology. Speed reduction is probably only economically feasible if policy incentives, such as CO2 trading or emissions charges are introduced. A significant shift from a primarily diesel-only fleet to a fleet that uses alternative fuels and energy sources cannot be expected until 2020, as most of the promising alternative
34 1 mph = 1.6 km/h 35 In fact four segments covering 80% of the fuel consumption were assessed: tank, bulk, container and general cargo ships.
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techniques are not yet tested to an extent that they can compete with diesel engines (Eyring et al., 2005b). Furthermore, the availability of alternative fuels is currently limited and time is needed to establish the infrastructure for alternative fuels. For these reasons, in the short term switching to alternative fuels provides a limited potential in general, but a significant potential for segments where a switch from diesel to natural gas is possible (Skjølsvik, 2005). Switching from diesel to natural gas has a 20% CO2 reduction potential and is being pursued as a measure in Norway for inland ferries and offshore supply vessels operating on the Norwegian Continental Shelf. The main obstacle to the increased utilization of natural gas is the access to LNG (Liquefied Natural Gas) and the technology’s level of costs compared to traditional ship solutions based on traditional fuel (Skjølsvik, 2005). A co-benefit of a switch from diesel to natural gas is that it also reduces emissions of SOx and NOx that contribute to local air pollution in the vicinity of ports. For the long-term (2050), the economical CO2 reduction potential might be large. One potential option is a combination of solar panels and sails. The use of large sails for super tankers is currently being tested in Germany and looks promising and may even be a cost-effective measure in the short term in case oil prices continue to soar. The use of large sails does not require fleet turnover but can be added to existing vessels (retrofit). The introduction of hydrogen-propelled ships and the use of fuel cell power at least for the auxiliary engines seem to be a possibility as well. For larger vessels capable and reliable fuel-cell-based ship propulsion systems are still a long way into the future, but might be possible in 2050 (Eyring et al., 2005b). Altmann et al. (2004) concluded that fuel cells offer the potential for significant environmental improvements both in air quality and climate protection. Local pollutant emissions and GHG emissions can be eliminated almost entirely over the full life cycle using renewable primary energies. The direct use of natural gas in high temperature fuel cells employed in large ships and the use of natural gas derived hydrogen in fuel cells installed in small ships allows for a GHG emission reduction of 20–40%.
5.4 Mitigation potential As discussed earlier, under ‘business-as-usual’ conditions with assumed adequate supplies of petroleum, GHG emissions from transport are expected to grow steadily during the next few decades, yielding about an 80% increase from 2002–2030 or 2.1% per year. This growth will not be evenly distributed; IEA projections of annual CO2 growth rates for 2002–2030 range from 1.3% for the OECD nations to 3.6% for the developing countries. The potential for reducing this growth will vary widely across countries and regions, as will the appropriate policies and measures that can accomplish such reduction.
Transport and its infrastructure
Analyses of the potential for reducing GHG emissions in the transport sector are largely limited to national or sub-national studies or to examinations of technologies at the vehicle level, for example well-to-wheel analyses of alternative fuels and drive trains for light-duty vehicles. The TAR presented the results of several studies for the years 2010 and 2020 (Table 3.16 of the TAR), with virtually all limited to single countries or to the EU or OECD. Many of these studies indicated that substantial reductions in transport GHG emissions could be achieved at negative or minimal costs, although these results generally used optimistic assumptions about future technology costs and/or did not consider trade-offs between vehicle efficiency and other (valued) vehicle characteristics. Studies undertaken since the TAR have tended to reach conclusions generally in agreement with these earlier studies, though recent studies have focused more on transitions to hydrogen used in fuel cell vehicles. This section will discuss some available studies and provide estimates of GHG emissions reduction potential and costs/tonne of carbon emissions reduced for a limited set of mitigation measures. These estimates do not properly reflect the wide range of measures available, many of which would likely be undertaken primarily to achieve goals other than GHG reduction (or saving energy), for example to provide mobility to the poor, reduce air pollution and traffic reduce congestion. The estimates do not include: • Measures to reduce shipping emissions; • Changes in urban structure that would reduce travel demand and enhance the use of mass transit, walking and bicycling; • Transport demand management measures, including parking ‘cash out’, road pricing, inner city entry charges, etc. 5.4.1
Available worldwide studies
Two recent studies – the International Energy Agency’s World Energy Outlook (IEA, 2004a) and the World Business Council on Sustainable Development’s Mobility 2030 (WBCSD, 2004a) – examined worldwide mitigation potential but were limited in scope. The IEA study focused on a few relatively modest measures and the WBCSD examined the impact of specified technology penetrations on the road vehicle sector (the study sponsors are primarily oil companies and automobile manufacturers) without regard to either cost or the policies needed to achieve such results. In addition, IEA has developed a simple worldwide scenario for light-duty vehicles that also explores radical reductions in GHG emissions. World Energy Outlook postulates an ‘Alternative scenario’ to their Reference scenario projection described earlier, in which vehicle fuel efficiency is improved, there are increased sales of alternative-fuel vehicles and the fuels themselves and demand side measures reduce transport demand and encourage a switch to alternative and less energy intensive transport modes. Some specific examples of technology changes and policy measures are:
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Well-to-Wheels GHG emissions, Gt CO2-eq
to-wheels GHG emissions per km than gasoline, with a 25% penetration by 2050; • Reduced travel demand, compared to the reference case, of 20% by 2050.
6
Short-term measures
4
FC with LowGHG-emission-H2
2 Remaining GHG emissions 0 2000
2010
2020
2030
2040
2050
Figure 5.14: Two possible scenarios for GHG reductions in Light-duty vehicles Source: IEA, 2004b.
• In the United States and Canada, vehicle fuel efficiency is nearly 20% better in 2030 than in the Reference scenario and hybrid and fuel-cell powered vehicles make up 15% of the stock of light-duty vehicles in 2030; • Average fuel efficiency in the developing countries and transition economies are 10–15% higher than in the Reference scenarios; • Measures to slow traffic growth and move to more efficient modes reduce road traffic by 5% in the European Union and 6% in Japan. Similarly, road freight is reduced by 8% in the EU and 10% in Japan. The net reductions in transport energy consumption and CO2 emissions in 2030 are 315 Mtoe, or 9.6% and 997 MtC, or 11.4%, respectively compared to the Reference scenario. This represents a 2002–2030 reduction in the annual growth rate of energy consumption from 2.1-1.3% per year, a significant accomplishment but one which still allows transport energy to grow by 57% during the period. CO2 emissions grow a bit less because of the shift to fuels with less carbon intensity, primarily natural gas and biofuels. IEA has also produced a technology brief that examines a simple scenario for reducing world GHG emissions from the transport sector (IEA, 2004b). The scenario includes a range of short-term actions, coupled with the development and deployment of fuel-cell vehicles and a low-carbon hydrogen fuel infrastructure. For the long-term actions, deployment of fuel-cell vehicles would aim for a 10% share of light-duty vehicle sales by 2030 and 100% by 2050, with a 75% per-vehicle reduction in GHG emissions by 2050 compared to gasoline vehicles. The short-term measures for light-duty vehicles are: • Improvements in fuel economy of gasoline and diesel vehicles, ranging from 15% (in comparison to the IEA reference case) by 2020 to 35% by 2050; • Growing penetration of hybrid vehicles, to 50% of sales by 2040; • Widespread introduction of biofuels, with 50% lower well358
Figure 5.14 shows the light-duty vehicle GHG emissions results of the scenario. The penetration of fuel cell vehicles by itself brings emissions back to their 2000-levels by 2050. Coupled with the nearer-term measures, GHG emissions peak in 2020 and retreat to half of their 2000-level by 2050. The Mobility 2030 study examined a scenario postulating very large increases in the penetration of fuel efficient technologies into road vehicles, coupled with improvements in vehicle use, assuming different time frames for industrialized and developing nations. The technologies and their fuel consumption and carbon emissions savings referenced to current gasoline ICEs were: Technology 1. Diesels 2. Hybridization 3. Biofuels
Carbon reduced/vehicle (%) 18 30 (36 for diesel hybrids) 20-80
4. Fuel cells with fossil hydrogen
45
5. Carbon-neutral hydrogen
100
Figure 5.15 shows the effect of a scenario postulating the market penetration of all of the technologies as well as an assumed change in consumer preferences for larger vehicles and improved traffic flows. The scenario assumes that diesels make up 45% of light-duty vehicles and medium trucks by 2030; that half of all sales in these vehicle classes are hybrids, also by 2030; that one-third of all motor vehicle liquid fuels are biofuels (mostly advanced) by 2050; that half of LDV and medium truck vehicle sales are fuel cells by 2050, with the hydrogen beginning as fossil-based but gradually moving to 80% carbon neutral by 2050; that better traffic flow and other efficiency measures reduce GHG emissions by 10%; and that the underlying efficiency of light-duty vehicles improves by 0.6% per year due to steady improvements (e.g., better aerodynamics and tyres) and to reduced consumer preference for size and power. In this scenario, GHG emissions return to their 2000-level by 2050. Mobility 2030’s authors make it quite clear that for this ‘mixed’ scenario to be even remotely possible will require overcoming many major obstacles. The introduction and widespread use of hydrogen fuel cell vehicles for example requires huge reductions in the costs of fuel cells; breakthroughs in on-board hydrogen storage; major advances in hydrogen production; overcoming the built-in advantages of the current gasoline and diesel fuel infrastructure; demonstration and commercialization of carbon
Chapter 5
Transport and its infrastructure
12
Gt CO2-eq
10
1 - Diesels (LDVs)
8
2 - Hybrids (LDVs + MDTs)
6
3 - Biofuels 80% low GHG sources 4 - Fuel Cells fossil hydrogen
4
5 - Fuel Cells 80% low-GHG H2
2
6 - Mix shifting 10% fuel efficiency improvement
Remaining GHG emissions
7 - 10% vehicle travel reduction all road vehicles
0 2000
2010
2020
2030
2040
2050
Figure 5.15: The effect of a scenario postulating the market penetration of all technologies Source: WBCSD, 2004a.
sequestration technologies for fossil fuel hydrogen production (at least if GHG emission goals are to be reached); and a host of other R&D, engineering and policy successes. Table 5.8 summarizes technical potentials for various mitigation options for the transport sector. As mentioned above, there are few studies dealing with worldwide analysis. In most of these studies, potentials are evaluated based on top-down scenario analysis. For combinations of specific power train technologies and fuels, well-to-wheels analyses are used to examine the various supply pathways. Technical potentials for operating practices, policies and behaviours are more difficult to isolate from economic and market potential and are usually derived from case studies or modelling analyses. Uncertainty is a key factor at all stages of assessment, from technology performance and cost to market acceptance. 5.4.2
Estimate of world mitigation costs and potentials in 2030
By extrapolating from recent analyses from the IEA and others an estimate can be given of the cost and potential for reducing transport CO2 emissions. This section covers improving the efficiency of light-duty vehicles and aircraft, and the substitution of conventional fossil fuels by biofuels throughout the transport sector (though primarily in road vehicles). As noted above, these estimates do not represent the full range of options available to reduce GHG emissions in the transport sector.
5.4.2.1
Light-duty Vehicles
The following estimate of the overall GHG emissions reduction potential and costs for improving the efficiency of the world’s light-duty vehicle fleet (thus reducing carbon emissions), is based on the IEA Reference Case, as documented in a spreadsheet model developed by the IEA for the Mobility 2030 project (WBSCD, 2004b). The cost estimates for total mitigation potential are provided in terms of ‘societal’ costs of reductions in GHG emissions, measured in US$/tonne of carbon (tC) or carbon dioxide (CO2); the costs are the net of higher vehicle costs minus discounted lifetime fuel savings. Fuel savings benefits are measured in terms of the untaxed cost of the fuels at the retail level, and future savings are discounted at a low societal rate of 4% per year. These costs are not the same as those that would be faced by consumers, who would face the full taxed costs of fuel, would almost certainly use a higher discount rate, and might value only a few years of fuel savings. Also, they do not include the consumer costs of forgoing further increases in vehicle performance and weight. Over the past few decades, increasing acceleration performance and vehicle weight have stifled increases in fuel economy for lightduty vehicles and these trends must be stopped if substantial progress is to be made in fleet efficiency. Because consumers value factors such as vehicle performance, stopping these trends will have a perceived cost – but there is little information about its magnitude. The potential improvements in light-duty fuel economy assumed in the analysis, and the costs of these improvements, are based on the scenarios in the MIT study summarised in Box 5.5. The efficiency improvements as mentioned in this study are 359
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Table 5.8: Summary table of CO2 mitigation potentials in transport sector taken from several studies Study
Mitigation measure/policy
Region
IEA 2004a
Alternative scenario
World OECD Developing countries Transition economies
IEA 2001
Improving Tech for Fuel Economy Diesel
OECD
IEA 2002a
All scenarios included All scenarios included All scenarios included
NA Western Europe Japan
IEA 2004d
Improving fuel economy Biofuels FCV with hydrogen refuelling COMBINING THESE THREE
World
IEA 2004b
Reduction in fuel use per km Blend of biofuels Reduction in growth of LDV travel using hydrogen in vehicle
World
ACEEE 2001
A-scenario B-scenario C-scenario
USA
MIT 2004
Baseline Medium HEV Composite
USA
CO2 reduction (%) 2010
2020
2030
2.2 2 2.8 2.3
6.8 6.9 6.8 6.2
11.4 11.5 11.4 11.2
30
40
CO2 reduction (Mt) 2050
2010
2020
2030
133 77 49 8
505 308 170 27
997 557 381 59
148 76 28
358 209 61
132 158 176
418 488 532
2050
5-15 6.6 6.6 8.3
14.4 15.6 16.1 18 12 7 30 15 5 5 0
9.9 11.8 13.2
25 8 10 3
35 13 20 75
26.3 30.6 33.4 (2035)
Combined policies Greene and Schafer 2003
14-24
32-50 18 3 2
Replacement & alternative fuels Low-carbon replacement fuels Hydrogen fuel (all LDV fuel)
2 1
7 4
Pricing policies Low-carbon fuel subsidy Carbon pricing Variabilization
2 3 6
6 6 9
Behavioural Land use & infrastructure System efficiency Climate change education Fuel economy information
3 0 1 1
5 1 2 1
22
48
USA
Total WEC 2004
New technologies
World
WBCSD 2004b
Road transport Diesels (LDVs) Hybrids (LDVs and MDTs) Biofuels-80% low GHG sources Fuel Cells-fossil hydrogen Fuel Cells-80% low-GHG hydrogen Mix shifting 10% FE improvement 10% Vehicle travel reductionall vehicles
World
360
16.8 29.9 44.4
(2015) 6 2 1
Efficiency standards Light-duty vehicles Heavy trucks Commercial aircraft
3-6
3.4 5.2 14.9
30
46
0.9 2.4 5.7 5.9 5.9
2.1 6.1 15.6 16.7 17.2
1.8 6.1 29.5 32.7 45.3
61 161 386 400 400
160 474 1207 1293 1333
181 623 3030 3364 4650
6.7
18.8
47.3
451
1455
4864
9.4
22.8
51.9
639
1765
5335
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Transport and its infrastructure
Box 5.5 Fuel economy benefits of multiple efficiency technologies Several studies have examined the fuel economy benefits of simultaneously applying multiple efficiency technologies to light-duty vehicles. However, most of these are difficult to compare because they examine various types of vehicles, on different driving cycles, using different technology assumptions, for different time frames. The Massachusetts Institute of Technology has developed such an assessment for 2020 (MIT, 2000) with documentation of basic assumptions though with few details about the specific technologies that achieve these values, for a medium size passenger car driving over the official US Environmental Protection Agency driving cycle (Heywood et al., 2003). There are two levels of technology improvement – ‘baseline’ and ‘advanced,’ with the latter level of improvement further subdivided into conventional and hybrid drive trains. Some of the key features of the 2020 vehicles are: • Vehicle mass is reduced by 15% (baseline) and 22% (advanced) by a combination of greater use of high strength steel, aluminium and plastics coupled with advanced design; • Tyre rolling resistance coefficient is reduced from the current .009 to .008 (baseline) and .006 (advanced); • Drag coefficient is reduced to 0.27 (baseline) and 0.22 (advanced). The baseline level is at the level of the best current vehicles, while the advanced level should be readily obtainable for the best vehicles in 2020, but seems quite ambitious for a fleet average; • Indicated engine efficiency increases to 41% in both baseline and advanced versions. This level of efficiency would likely require direct injection, full valve control (and possibly camless valves) and advanced engine combustion strategies. The combined effects of applying this full range of technologies are quite dramatic (Table 5.9). From current test values of 30.6 mpg (7.69 litres/100 km) as a 2001 reference, baseline 2020 gasoline vehicles obtain 43.2 mpg (5.44 L/100 km), advanced gasoline vehicles 49.2 mpg (4.78 L/100 km) and gasoline hybrids 70.7 mpg (3.33 L/100 km); advanced diesels obtain 58.1 mpg (4.05 L/100 km) and diesel hybrids 82.5 mpg (2.85 L/100 km) (note that on-road values will be at least 15% lower). In comparison, Ricardo Consulting Engineers (Owen and Gordon, 2002) estimate the potential for achieving 92 g/km CO2 emissions, equivalent to 68.6 mpg (3.43 L/100 km), for an advanced diesel hybrid medium size car ‘without’ substantive non-drive train improvements. This is probably a bit more optimistic than the MIT analysis when accounting for the additional effects of reduced vehicle mass, tyre rolling resistance and aerodynamic drag coefficient. These values should be placed in context. First, the advanced vehicles represent ‘leading edge’ vehicles which must then be introduced more widely into the new vehicle fleet over a number of years and may take several years (if ever) to represent an ‘average’ vehicle. Second, the estimated fuel economy values are attainable only if trends towards ever-increasing vehicle performance are stifled; this may be difficult to achieve.
discounted somewhat to take into account the period in which the full benefits can be achieved. Further, fleet penetration of the technology advances are assumed to be delayed by 5 years in developing nations; however, because developing nation fleets are growing rapidly, higher efficiency vehicles, once introduced, may become a large fraction of the total fleet in these nations within a relatively short time. The technology assumptions for two ‘efficiency scenarios’ are as follows (Table 5.9a). The high efficiency and medium efficiency scenarios achieve the following improvements in efficiency for the new light-duty vehicle fleet (Table 5.9b): Table 5.10 shows the light-duty vehicle fuel consumption and (vehicle only) CO2 emissions for the Reference scenario and the High and medium efficiency scenarios. In the Reference case, LDV fuel consumption increases by nearly 60% by 2030; the High Efficiency Case cuts this increase to 26% and the Medium efficiency scenario cuts it to 42%. For the OECD nations, the Reference Case projects only a 22% increase by 2030, primarily
because of moderate growth in travel demand, with the High efficiency scenario actually reducing fuel consumption in this group of nations by 9% and the Medium efficiency scenario reducing growth to only 6%. This regional decrease (or modest increase) in fuel use is overwhelmed by the rapid growth in the world’s total fleet size and overall travel demand and the slower uptake of efficiency technologies in the developing nations. Because no change in the use of biofuels was assumed in this analysis, the CO2 emissions in the scenarios essentially track the energy consumption paths discussed above. Figure 5.16 shows the GHG emissions path for the three scenarios, resulting in a mitigation potential of about 800 (High) and 400 (Medium) MtCO2 in 2030. Table 5.11 shows the cost of the reductions in GHG emissions in US$/tCO2 for those reductions obtained by the 2030 new vehicle fleet over its lifetime, assuming oil prices of 30 US$, 40 US$, 50 US$ and 60 US$/bbl over the vehicles’ lifetime.36 Note that the costs in Table 5.11 do not apply to the carbon reductions achieved in that year by the entire LDV fleet (from Table 361
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Table 5.9a: Fuel economy and cost assumptions for cost and potentials analysis Medium size car
MPG (L/100 km)
Incr from Ref (%)
Cost (%)
ΔCost (US$)a)
2001 reference
30.6 (7.69)
0
100
0
2030 baseline
43.2 (5.55)
41
105
1,000
2030 advanced
49.2 (4.78)
61
113
2,600
2030 hybrid
70.7 (3.33)
131
123
4,600
2030 diesel
58.1 (4.05)
90
119
3,800
2030 diesel hybrid
82.5 (2.85)
170
128
5,600
a) Cost differential based on a reference 20,000 US$ vehicle. See Box 5.5 for the definitions of the vehicle types. Source: adapted from MIT (2000), as explained in the text.
Table 5.9b: Efficiency improvements new light-duty vehicle fleet Region
% improvement from 2001 levels, high/medium 2015
2020
2025
2030
North America
30/15
45/25
70/32
80/40
Europe
30/25
40/30
55/35
70/40
Emerging Asia/Pacific
30/25
40/30
65/35
75/40
Rest of world
0/12+
30/20+
45/25+
60/30+
5.10), because those reductions are associated with successive waves of high efficiency vehicles entering the fleet during the approximately 15 year period before (and including) 2030. The Table 5.11 results show that the ‘social cost of carbon reduction’ for light-duty vehicles varies dramatically across regions and with fuel prices (since the cost is the net of technology costs minus the value of fuel savings). The results are also quite different for the High and Medium efficiency scenarios, primarily because the estimated technology costs begin to rise more steeply at higher efficiency levels, raising the average cost/tonne of CO2 in the High efficiency scenario. For the High efficiency scenario, CO2 reduction costs are very high for the OECD countries aside from North America, even at 60 US$/bbl oil prices, reflecting the ambitious (and expensive) increases in that scenario, the relatively high efficiencies of those regions’ fleets in the Reference Case, and the relatively low km/vehicle/year driven outside North America; on the other hand, the costs of the moderate increases in the Medium efficiency scenario are low to negative for all regions, reflecting the availability of moderate cost technologies capable of raising average vehicle efficiencies up to 30–40% or so. The values in Table 5.11 are sensitive to several important assumptions: • Technology costs: the costs assumed here appear to be considerably higher than those assumed in WEO 2006 (IEA, 2006a).
•
•
•
Discount rates: the analysis assumes a low social discount rate of 4% in keeping with the purpose of the analysis. As noted, vehicle purchasers would undoubtedly use higher rates and would value fuel savings at retail fuel prices rather than the untaxed values used here; they might also only value a few years of fuel savings rather than the lifetime savings assumed here. WEO 2006 on the other hand, used a zero discount rate, substantially reducing the net cost of carbon reduction. Vehicle km travelled (vkt): this analysis used the IEA/ WBCSD spreadsheet’s assumption of constant vkt over time and applied these values to new cars. Actual driving patterns will depend on the balance of increasing road infrastructure and rapidly increasing fleet size in developing nations. Unless infrastructure keeps pace with growing fleet size, which will be difficult, the assumption of constant vkt/ vehicle may prove accurate or even optimistic. Efficiency gains assumed in the Reference scenario: the Reference scenario assumed significant gains in most areas (aside from North America), which makes the Efficiency scenarios more expensive.
Table 5.12 shows the economic potential for reducing CO2 emissions in the 2030 fleet of new LDVs as a function of world oil price.37 The values show that much of the economic potential is available at a net savings, ‘if consumer preference for power and other efficiency-robbing vehicle attributes is ignored’. Even at 30 US$/bbl oil prices, over half of the total
36 Note, however, that these results do not take into account changes in travel demand that would occur with changing fuel price and changes in Reference case vehicle efficiency levels. At higher oil prices, the Reference case would likely have less travel and higher vehicle efficiency; this would, in turn, reduce the oil savings and GHG reductions obtained by the Efficiency case and would likely raise the costs/tonne C from the values shown here.
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Table 5.10: Regional and worldwide Light-duty vehicle CO2 emissions (vehicle only) and fuel consumption, efficiency and reference cases CO2 emissions (Mt) 2000
OECD North America
Energy use (EJ)
2030
2030
Reference
High
Medium
2000
Reference
High
Medium
1226
1623
1178
1392
17.7
23.4
17.0
20.0
OECD Europe
488
535
431
479
7.0
7.5
6.0
6.7
OECD Pacific
220
219
176
197
3.2
3.2
2.6
2.9
84
229
188
209
1.2
3.3
2.7
3.0
EECCA Eastern Europe
49
82
68
74
0.7
1.2
1.0
1.0
China
46
303
267
287
0.7
4.4
3.8
4.1
Other Asia
54
174
148
160
0.8
2.5
2.1
2.3
India
22
103
87
95
0.3
1.5
1.2
1.4
Middle East
27
67
57
62
0.4
1.0
0.8
0.9
Latin America
110
294
251
273
1.6
4.2
3.6
3.9
53
167
152
162
0.8
2.4
2.2
2.3
2379
3797
3004
3390
34.2
54.4
43.1
48.6
Africa Total
Note: EECCA = countries of EasternEurope, the Caucasus and Central Asia.
Table 5.11: Cost of CO2 reduction in new 2030 LDVs CO2 reduction cost (US$/tCO2) High efficiency case 30 US$/bbl 0.39 US$/L
Medium efficiency case
40 US$/bbl 0.45 US$/L
50 US$/bbl 0.51 US$/L
60 US$/bbl 0.60 US$/L
5
-16
-37
-68
OECD Europe
131
110
89
OECD Pacific
231
210
81
OECD North America
EECCA Eastern Europe
30 US$/bbl 0.39 US$/L
40 US$/bbl 0.45 US$/L
50 US$/bbl 0.51 US$/L
60 US$/bbl 0.60 US$/L
-72
-93
-114
-146
58
14
-7
-28
-60
189
157
-14
-36
-57
-88
60
39
8
-54
-76
-97
-128
181
160
139
107
-18
-39
-60
-92
China
23
2
-19
-51
-23
-44
-65
-97
Other Asia
19
-2
-23
-55
-23
-44
-65
-96
India
62
41
20
-12
9
-12
-33
-65
Middle East
-15
-36
-57
-89
-49
-70
-91
-122
Latin America
-6
-27
-48
-79
-42
-63
-84
-116
Africa
10
-12
-33
-64
-33
-54
-75
-106
Note: EECCA = countries of EasternEurope, the Caucasus and Central Asia.
(<100 US$/tCO2) potential is available at a net savings over the vehicle lifetime; at 40 US$/bbl, over 90% of the 718 Mt total potential is available at a net savings. The regional detail, not shown in Table 5.12, is illuminating. In the High Efficiency scenario, of 793 Mt of total potential,
445 Mt are in OECD North America and are available at a net savings at 40 US$/bbl oil (and at less than 20 US$/tCO2 at 30 US$/bbl oil). The next highest regional potential is in OECD Europe at 104 Mt, but this potential is more expensive: at 30 US$/bbl oil. Only 56 Mt is available below 100 US$/tCO2, and becomes available at below 100 US$/tCO2 only at 60 US$/bbl
37 These results do not take account of the effect higher oil prices would have on LDV efficiency in the Reference Scenario. This efficiency level would be expected to be a strong function of oil price, that is, it would be higher for higher prices. Consequently, the technology cost of improving vehicle efficiency further would also be higher – reducing the economic potential.
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Transport and its infrastructure
4.0
Chapter 5
Gt CO2 Reference
3.5 Medium Efficiency High Efficiency
3.0
•
2.5
2000
2010
2020
2030
Figure 5.16: Light-duty vehicle CO2 emissions for three scenarios
oil. China has the next highest total emissions (2030 Reference case emissions of 303 Mt) but only a moderate potential of 36 Mt. This potential is fully available at a net savings only if oil is 50 US$/bbl or higher – perhaps not surprising because China has ambitious fuel economy standards embedded in the Reference Case and has relatively low driving rates, which make further improvements more difficult and expensive.
5.4.2.2
Aircraft
QinetiQ (UK)38 analysed the fuel consumption and CO2 trends for a simple global aviation growth scenario to provide an indicative view on the extent that technology and other developments might mitigate aviation emissions. The ICAO traffic forecast (ICAO/FESG, 2003) defined traffic growth to 2030 from which a future fleet composition was developed, using a range of current and future aircraft types where their introduction could be assumed, as well as representative aircraft types based on seat capacity. Fuel burn and emissions were calculated using known emissions performance and projections for future aircraft where necessary. The analysis assumed a range of technology options as follows: • Case 1 assumed no technology change from 2002 to 2030; using the extrapolated traffic forecast from ICAO FESG – this case shows only the effects of traffic growth on emissions. • Case 2 – as Case 1, but assumes all new aircraft deliveries after 2005 would be ‘best available technology at a 2005 (BAT)’ performance standard, and with specific new aircraft (A380, A350, B787) delivered from 2008. • Case 3 – as Case 1, but with assumed annual fleet fuel efficiency improvements as per ‘Greene’ and DTI (IPCC 38 http://www.dti.gov.uk/files/file35675.pdf
364
•
1999, Chapter 9, Table 9.15). This assumes a fleet efficiency improvement trend of 1.3% per year to 2010, assumed then to decline to 1.0% per year to 2020 and 0.5% per year thereafter. This is the reference case. Case 4 – as Case 3, plus the assumption that a 50 US$/tCO2 cost will produce a further 0.5% fuel efficiency improvement per annum from 2005, as suggested by the cost-potential estimates of Wit et al., (2002), that assume technologies such as winglets, fuselage skin treatments (riblets) and further weight reductions and engine developments will be introduced by airlines. Case 5 – as Case 3, plus the assumption of 100 US$/tCO2 cost, producing a 1.0% fuel efficiency improvement per annum from 2005 (Wit et al., 2002), again influencing the introduction of additional technologies as above. The results of this analysis are summarised in Table 5.13.
Case 2 is a simple representation of planned industry developments and shows their effect to 2030, ignoring further technology developments. This is an artificial case, as on-going efficiency improvements would occur as a matter of course, but it shows that these planned fleet developments alone might save 14% of the CO2 that the ‘no technology change’ of Case 1 would have produced. Case 3 should be regarded as the ‘base case’ from which benefits are measured, as this case reflects an agreed fuel efficiency trend assumed for some of the calculations produced in the IPCC Special Report (1999). This results in a further 11% reduction in CO2 by 2030 compared with Case 2. Cases 4 and 5 assume that a carbon cost will drive additional technology developments from 2005 – no additional demand effect has been assumed. These show further CO2 reduction of 11.8% and 22.2% compared with ‘base case’ 3 over the same period from technologies that are assumed to be more attractive than hitherto. However, even the most ambitious scenario suggests that CO2 production will increase by almost 100% from the base year. The cost potentials for Cases 4 and 5 are based on one study and further studies may refine these results. There is limited literature in the public domain on costs of mitigation technologies. The effects of more advanced technology developments, such as the blended wing body, are not modelled here, as these developments are assumed to take place after 2030. The analysis suggests that aviation emissions will continue to grow as a result of continued demand for civil aviation. Assuming the historical fuel efficiency trend produced by industry developments will continue (albeit at a declining level), carbon emissions will also grow, but at a lower rate than traffic. Carbon pricing could effect further emissions reductions if the aviation industry introduces further technology measures in response.
Chapter 5
Transport and its infrastructure
Table 5.12: Economic potential of LDV mitigation technologies as a function of world oil price, for new vehicles in 2030 World oil price (US$/bbl)
Region
Economic potential (MtCO2) Cost ranges (US$/tCO2) <100
<0
0-20
20-50
50-100
30
OECD EIT Other World
523 49 146 718
253 28 88 369
270 0 30 300
0 0 20 20
0 21 8 29
40
OECD EIT Other World
523 49 146 718
523 28 118 669
0 0 20 20
0 0 8 8
0 21 0 21
50
OECD EIT Other World
571 49 146 766
523 28 138 689
0 0 8 8
0 21 0 21
48 0 0 48
60
OECD EIT Other World
571 49 146 766
523 28 146 697
0 21 0 21
0 0 0 0
48 0 0 48
5.4.2.3
Biofuels
breakthroughs, biofuels use in road transport would double compared to the Alternative policy scenario.
IEA has projected the potential worldwide increased use of biofuels in the transport sector assuming successful technology development and policy measures reducing barriers to biomass deployment and providing economic incentives. IEA’s World Energy Outlook 2006 (IEA, 2006b) develops an Alternative policy scenario that adds 55 Mtoe biofuels above baseline levels of 92 Mtoe by 2030, which increases the biofuels share of total transport fuel demand from 3 to 5%. In this scenario, all of the biofuels are produced by conventional technology, that is ethanol from starch and sugar crops and biodiesel from oil crops. Assuming an average CO2 reduction from gasoline use of 25%,39 this would reduce transport CO2 emissions by 36 Mt. Furthermore, according to the Beyond the Alternative policy scenario (BAPS), which assumed more energy savings and emission reductions through a set of technological
A second IEA report, Energy Technology Perspectives 2006 (IEA, 2006a), evaluates a series of more ambitious scenarios that yield biomass displacement of 13–25% of transport energy demand by 2050, compared to Baseline levels of 3% displacement. Two scenarios, called Accelerated Technology (ACT) Map and TECH Plus, assume economic incentives equivalent to 25 US$/tCO2, increased support for research and development, demonstration, and deployment programmes, and policy instruments to overcome commercialization barriers. Both scenarios have optimistic assumptions about the success of efforts to reduce fuel production costs, increase crop yields, and so forth. In the ACT Map scenario, transport biofuels production reaches 480 Mtoe in 2050, accounting for 13% of total transport demand; in TECH Plus, biofuels represents 25% of transport energy demand by 2050. These displacements yield CO2 reductions (below the Baseline levels) of 1800 MtCO2 in Map and 2300 MtCO2 in TECH Plus, with the major
Table 5.13: Summaries of CO2 mitigation potential analysis in aviation Aviation technology
2002 CO2 (Mt)
2030 CO2 (Mt)
Ratio (2030/2002)
Case 1 (no technological change)
489.29
1,609.74
3.29
Case 2 (BAT new aircrafts)
489.29
1,395.06
2.85
Case 3 (base)
489.29
1,247.02 (100%)
2.55
Case 4 (50 US$/tCO2-eq)
489.29
1,100.15 (88%)
2.25
Case 5 (100 US$/tCO2-eq)
489.29
969.96 (78%)
1.98
39 IEA cites the following estimates for biofuels CO2 reduction when used as a replacement fuel: Corn in the U.S., –13%; ethanol in Europe, –30%; ethanol in Brazil, –90%; sugar beets to ethanol in Europe, –40 to –60%; rapeseed-derived biodiesel in Europe, –40 to –60%.
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Transport and its infrastructure
contributors being biodiesel from Fischer Tropsch conversion and ethanol from both sugar crops and cellulosic feedstocks; biodiesel from vegetable oil and ethanol from grains represent somewhat lower shares. Although the report does not provide quantitative estimates of CO2 reduction in 2030, it presents qualitative information (Table 3.5 of the IEA report) that implies that 2030-levels of biodiesel from vegetable oil and ethanol from grain and sugar crops are similar to 2050-levels, but biodiesel from Fischer Tropsch conversion, a major source in 2050, plays little role in 2030 and cellulosic ethanol is also significantly lower in 2030 than in 2050. The implied 2030 potential from the two scenarios appears to be about 600–1500 MtCO2. 5.4.2.4
Totals
The estimates discussed above can be summarized as follows: Light-duty vehicles: 718–766 MtCO2 at carbon prices less than 100 US$/tCO2 689–718 MtCO2 at carbon prices less than 50 US$/tCO2 669–718 MtCO2 at carbon prices less than 20 US$/tCO2 369–697 MtCO2 at carbon prices less than 0 US$/tCO2 Aircraft: 150 MtCO2 at carbon prices less than 50 US$/tCO2 280 MtCO2 at carbon prices less than 100 US$/tCO2 Biofuels: 600–1500 MtCO2 at carbon prices less than 25 US$/tCO2 Although presumably the potential for biofuels penetration would be higher above the cited 25 US$/tCO2 carbon price, the total potential for a carbon price of 100 US$/tCO2 for the three mitigation sources is about 1600–2550 MtCO2. Much of this potential appears to be located in OECD North America and Europe. Note, however, that the potential is measured as the ‘further’ reduction in CO2 emissions from the Reference scenario, which assumes that substantial amounts of biofuels will be produced in Brazil and elsewhere and significant improvements in fuel efficiency will occur in China and in other industrializing nations without further policy measures.
5.5 Policies and measures This section provides policies and measures for the transport sector, considering experiences of countries and regions in achieving both energy savings (and hence GHG reduction) and sustainable transport systems. An overall policy consideration at the national level and international levels is presented in Chapter 13.3 The policies and measures that have been considered in this section that are commonly applied for the sector and can be effective are: 366
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• • • • • • •
Land use and transport planning; Taxation and pricing; Regulatory and operational instruments (e.g., traffic management, control and information); Fuel economy standards – road transport; Transport demand management; Non-climate policies influencing GHG emissions; Co-benefits and ancillary benefits.
This section discusses climate policies related to GHG from international aviation and shipping separately, reflecting the international coordination that is required for effective reduction strategies in these sectors. Both sectors are subject to a global legal framework and mitigation policies applied on a unilateral basis may reduce its environmental effectiveness due to evasion (Wit et al., 2004). 5.5.1
Surface transport
A wide array of policies and strategies has been employed in different circumstances around the world to restrain vehicle usage, manage traffic congestion and reduce energy use, GHGs, and air pollution. There tends to be considerable overlap among these policies and strategies, often with synergistic effects. The recent history almost everywhere in the world has been increasing travel, bigger vehicles, decreasing land-use densities and sprawling cities. But some cities are far less dependent on motor vehicles and far denser than others, even at the same incomes. The potential exists to greatly reduce transport energy use and GHG emissions by shaping the design of cities, restraining motorization and altering the attributes of vehicles and fuels. Indeed, slowing the growth in vehicle use through land-use planning and through policies that restrain increases in vehicle use would be an important accomplishment. Planning and policy to restrain vehicles and densify land use not only lead to reduced GHG emissions, but also reduced pollution, traffic congestion, oil use, and infrastructure expenditures and are generally consistent with social equity goals as well. 5.5.1.1
Land use and transport planning
Energy use for urban transport is determined by a number of factors, including the location of employment and residential locations. In recent decades, most cities have been increasing their dependence on the automobile and decreasing dependence on public transport. In some cases increasing motorization is the result of deliberate planning – what became known as ‘predict and provide’ (The Royal Commission on Transport and the Environment, 1994; Goodwin, 1999). This planning and programming process played a central role in developed countries during the second half of the 20th century. In many developing countries, the process of motorization and road building is less organized, but is generally following the same motorization path, often at an accelerated rate.
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non motorised
motorised public
motorised private
U.S.A. Australia/New Zealand Canada Western Europe High Income Asia Eastern Europe Middle East Latin America Africa Low Income Asia China 0
20
40
60
80
100%
Figure 5.17: Modal split for the cities represented in the Millennium Cities Database for Sustainable Transport by region Source: Kenworthy & Laube, 2002.
Income plays a central role in explaining motorization. But cities of similar wealth often have very different rates of motorizsation. Mode shares vary dramatically across cities, even within single countries. The share of trips by walking, cycling and public transport is 50% or higher in most Asian, African and Latin American cities, and even in Japan and Western Europe (Figure 5.17). Coordination of land use and transport planning is key to maintaining these high mode shares. Kenworthy and Laube (1999) pointed out that high urban densities are associated with lower levels of car ownership and car use and higher levels of transit use. These densities are decreasing almost everywhere. Perhaps the most important strategy and highest priority to slow motorization is to strengthen local institutions, particularly in urban areas (Sperling and Salon, 2002). Some Asian cities with strong governments, especially Hong Kong, Singapore and Shanghai are actively and effectively pursuing strategies to slow motorization by providing high quality public transport and coordinating land use and transport planning (Cullinane, 2002; Willoughby, 2001; Cameron et al., 2004; Sperling and Salon, 2002). There are many other examples of successfully integrated land use and transport planning, including Stockholm and Portland, Oregon (USA) (Abbott, 2002; Lundqvist, 2003). They mostly couple mixed-use and compact land use development with better public transport access to minimize auto dependence. The effectiveness of these initiatives in reducing sprawl is the subject of debate, especially in the USA (Song and Knaap, 2004; Gordon and Richardson, 1997; Ewing, 1997). There are several
arguments that the settlement pattern is largely determined, so changes in land use are marginal, or that travel behaviour may be more susceptible to policy interventions than land-use preferences (Richardson and Bae, 2004). Ewing and Cervero (2001) found that typical elasticity of vehicle-km travelled with respect to local density is –0.05, while Pickrell (1999) noted that reduction in auto use become significant only at densities of 4000 people or more per square kilometre – densities rarely observed in US suburbs, but often reached elsewhere (Newman and Kenworthy, 1999). Coordinated transport and land-use methods might have greater benefits in the developing world where dense mixed land use prevails and car ownership rate is low. Curitiba is a prime example of coordinated citywide transport and land-use planning (Gilat and Sussman, 2003; Cervero, 1998). The effectiveness of policies in shifting passengers from cars to buses and rails is uncertain. The literature on elasticity with respect to other prices (cross price elasticity) is not abundant and likely to vary according to the context (Hensher, 2001). The Transport Research Laboratory guide showed several cross price elasticity estimates with considerable variance in preceding studies (TRL, 2004). Goodwin (1992) gave an average cross elasticity of public transport demand with respect to petrol prices of +0.34. Jong and Gunn (2001) also gave an average cross elasticity of public transport trips with respect to fuel price and car time of +0.33 and +0.27 in the short term and +0.07 and +0.15 in the long term. The literature on mode shifts from cars to new rail services is also limited. A monitoring study of Manchester indicated that about 11% of the passengers on the new light rail would have 367
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Table 5.14: Taxes and pricing in the transport sector in developing and developed countries Instrument
Developing countries/EIT
Developed countries
Tax incentives to promote use of natural gas
Pakistan, Argentina, Colombia, Russia
Italy, Germany, Australia, Ireland, Canada, UK, Belgium
Incentives to promote natural gas vehicles
Malaysia, Egypt
Belgium, UK, USA, Australia, Ireland
Annual road tax differentiated by vintage
Singapore and India (fixed span and scrapping)
Germany
Emission trading
Chile
Congestion pricing including Area Licensing Scheme; vehicle registration fees; annual circulation tax
Chile, Singapore
Norway, Belgium
Vehicle taxes based on emissions-tax deductions on cleaner cars e.g., battery operated or alternative fuel vehicles
South Korea
Austria, Britain, Belgium, Germany, Japan, The Netherlands, Sweden
Carbon tax by size of engine
Zimbabwe
Cross subsidization of cleaner fuels (ethanol blending by gasoline tax - through imposition of lower surcharge or excise duty exemption)
India
Source: Adapted from Pandey and Bhardwaj, 2000; Gupta, 1999 and European Natural Gas Vehicle Association, 2002.
otherwise used their cars for their trips (Mackett and Edwards, 1998), while a Japanese study of four domestic rails and monorails showed that 10–30% of passengers on these modes were diverted from car mode. The majority of the passengers were transferred from alternative bus and rail routes (Japanese Ministry of Land, Infrastructure and Transport and Institute of Highway Economics, 2004). The Transport Research Laboratory guide (2004) contained international evidence of diversion rates from car to new urban rail ranging from 5–30%. These diversion rates are partly related to car mode share, in the sense that car share is so high in the USA and Australia that ridership on new rail systems is more likely to come from cars in those countries (Booz Allen & Hamilton 1999, cited in Transport Research Laboratory, 2004). It is also known that patronage of metros for cities in the developing world has been drawn almost exclusively from existing public transport users or through generation effects (Fouracre et al., 2003). The literature suggests that in general, single policies or initiatives tend to have a rather modest effect on the motorization process. The key to restraining motorization is to cluster a number of initiatives and policies, including improved transit service, improved facilities for NMT (Non-motorized transport) and market and regulatory instruments to restrain car ownership and use (Sperling and Salon, 2002). Various pricing and regulatory instruments are addressed below. Investment appraisal is an important issue in transport planning and policy. The most widely applied appraisal technique in transport is cost benefit analysis (CBA) (Nijkamp et al., 2003). In CBA, the cost of CO2 emissions can be indirectly included in the vehicle operating cost or directly counted at an estimated price, but some form of robustness testing is useful in the latter case. Alternatively, the amount of CO2 emissions is 368
listed on an appraisal summary table of Multi-Criteria Analysis (MCA) as a part of non-monetized benefits and costs (Mackie and Nellthorp, 2001; Grant-Muller et al., 2001; Forkenbrock and Weisbrod, 2001; Japanese Study Group on Road Investment Evaluation, 2000). To the extent that the cost of CO2 emissions has a relatively important weight in these assessments, investments in unnecessarily carbon-intensive projects might be avoided. Strategic CBA can further make transport planning and policy carbon-efficient by extending CBA to cover multimodal investment alternatives, while Strategic Environmental Assessment (SEA) can accomplish it by including multi-sector elements. (ECMT, 2000; ECMT, 2004b). 5.5.1.2
Taxation and pricing
Transport pricing refers to the collection of measures used to alter market prices by influencing the purchase or use of a vehicle. Typically measures applied to road transport are fuel pricing and taxation, vehicle license/registration fees, annual circulation taxes, tolls and road charges and parking charges. Table 5.14 presents an overview of examples of taxes and pricing measures that have been applied in some developing and developed countries. Pricing, taxes and charges, apart from raising revenue for governments, are expected to influence travel demand and hence fuel demand and it is on this basis that GHG reduction can be realized. Transport pricing can offer important gains in social welfare. For the UK, France and Germany together, (OECD, 2003) estimates net welfare gains to society of optimal charges (set at the marginal social cost level) at over 20 billion €/yr (22.6 US$/yr).
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Box 5.6 Examples of pricing policies for heavy-duty vehicles Switzerland: In January 2001, trucks of maximum 35 tonnes weight were allowed on Swiss territory (previously 28 tonnes) and a tax of 1.00 cent/tkm (for the vehicle middle emission category) was imposed on trucks above 3.5 tonnes on all roads. It replaced a previous fixed tax on heavy-duty vehicles. The tax is raised electronically. Since 2005, the tax is higher at 1.60 cent/tkm, but 40 tonnes trucks are allowed. Over the period 2001–2003, it was estimated that it contributed to an 11.9% decrease in vehicle-km and a 3.5% decrease in tonnes-km of domestic traffic. The tax led to an improved carriers’ productivity and it is anticipated that, for that reason, emissions of CO2 and NOx would decrease over the period 2001–2007 by 6–8%. On the other hand transit traffic, which amounts to 10% of total traffic, was also affected in a similar way by the new tax regime, so that the number of HDL has been decreasing at a rate of about 2–3% per year, while, at the same time, increasing in terms of tonnes-km (ARE, 2004b; 2006). A part of the revenues are used to finance improvements to the rail network. Germany: A new toll system was introduced in January 2005 for all trucks with a maximum weight of 12 tonnes and above. This so-called LKW-MAUT tax is levied on superhighways on the base of the distance driven; its cost varies between 9 and 14 Eurocents according to the number of axles and the emission category of the truck. Payments are made via a GPS system, at manual payment terminals or by Internet. The receipts will be used to improve the transport networks of Germany. The system introduction appears successful, but it is too early to assess its impacts.
Although the focus here is on transport pricing options to limit CO2 emissions, it should be recognized that many projects and policies with that effect are not focused on GHG emissions but rather on other objectives. A pricing policy may well aim simultaneously at reducing local pollution and GHG emissions, accidents, noise and congestion, as well as generating State revenue for enlarging of social welfare and/or infrastructure construction and maintenance. Every benefit with respect to these objectives may then be assessed simultaneously through CBA or MCA; they may be called co-benefits. Governments can take these co-benefits into account when considering the introduction of transport pricing such as for fuel. This is all the more important since a project could be not worth realising if only one particular benefit is considered, whereas it could very well be proved beneficial when adding all the co-benefits. Taxes Empirically, throughout the last 30 years, regions with relatively low fuel prices have low fuel economy (USA, Canada, Australia) and regions where relatively high fuel prices apply (due to fuel taxes) have better car fuel economy (Japan and European countries). For example, fuel taxes are about 8 times higher in the UK than in the USA, resulting in fuel prices that are about three times higher. UK vehicles are about twice as fuel-efficient; mileage travelled is about 20% lower and vehicle ownership is lower as well. This also results in lower average per capita fuel expenditures. Clearly, automobile use is sensitive to cost differences in the long run (VTPI, 2005). In theory, long run impact of increases in fuel prices on fuel consumption are likely to be about 2 to 3 times greater than short run impact (VTPI, 2005). Based on the price elasticities (Goodwin et al., 2004) judged to be the best defined results for developed countries, if the real price of fuel rises by 10% and stays at that level, the volume of fuel consumed by road vehicles will fall by about 2.5% within a year, building up to a
reduction of over 6% in the longer run (about 5 years or so), as shown in Table 5.15. An important reason why a fuel or CO2 tax would have limited effects is that price elasticities tend to be substantially smaller than the income elasticities of demand. In the long run the income elasticity of demand is a factor 1.5–3 higher than the price elasticity of total transport demand (Goodwin et al., 2004). In developing countries, where incomes are lower, the demand response to price changes may be significantly more elastic. Recent evidence suggests that the effect of CO2 taxes and high fuel prices may be having a shrinking effect in the more car-dependent societies. While the evidence is solid that price elasticities indicated in Table 5.15 and used by Goodwin were indeed around –0.25 (i.e., 2.5% reduction in fuel for every 10% increase in price), in earlier years, new evidence indicates a quite different story. Small and Van Dender (2007) found that price elasticities in the USA dropped to about –0.11 in the late 1990s, and Hughes et al. (2006) found that they dropped even further in 2001–2006, to about –0.04. The explanation seems to be that people in the USA have become so dependent on their vehicles that they have little choice but to adapt to higher prices. One might argue that these are short term elasticities, but the erratic nature of gasoline prices in the USA (and the world) result in drivers never exhibiting long-term behavior. Prices drop before they seriously consider changing work or home locations or even buying more efficient vehicles. If oil prices continue to cycle up and down, as many expect, drivers may continue to cling to their current behaviors. If so, CO2 taxes would have small and shrinking effects in the USA and other countries where cars are most common.
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Table 5.15: Impact of a permanent increase in real fuel prices by 10% Short run/within 1 year (%) Traffic volume
Long run/5 years (%)
-1
-3
Fuel consumption
-2.5
-6
Vehicle fuel efficiency
-1.5
-4
Less than -1
-2.5
Vehicle ownership Source: Goodwin et al. 2004.
As an alternative to fuel taxes, registration and circulation taxes can be used to incentivise the purchase (directly) and manufacturing (indirectly) of fuel-efficient cars. This could be done through a revenue neutral fee system, where fuel-efficient cars receive a rebate and guzzler cars are faced with an extra fee. There is evidence that incentives given through registration taxes are more effective than incentives given through annual circulation taxes (Annema et al., 2001). Buyers of new cars do not expect to be able to pass on increased registration taxes when selling the vehicle. Due to refunds on registration taxes for cars that were relatively fuel efficient compared to similar sized cars, the percentage of cars sold in the two most fuel efficient classes increased from 0.3%–3.2% (cars over 20% more fuel efficient than average) and from 9.5%–16.1% (for cars between 10 and 20% more fuel efficient than average) in the Netherlands (ADAC, 2005). After the abolishment of the refunds, shares decreased again. COWI (2002) modelled the impact on fuel efficiency of reforming current registration and circulation taxes so they would depend fully on the CO2 emissions of new cars. Calculated reduction percentages varied from 3.3–8.5% for 9 European countries, depending on their current tax bases.
responsibility for GHG emissions from the road transport sector, which they supply with fuel. As of 1 October 2005, Swiss oil importers voluntarily contribute the equivalent of about 5 cents per gallon (approx. 80 million US$ annually) into a climate protection fund that is invested via a non-profit (non-governmental) foundation into climate mitigation projects domestically and abroad (via the emerging carbon market mechanisms of the Kyoto Protocol). Cost savings (compared with an incentive tax) are huge and the private sector is in charge of investing the funds effectively. A similar system in the USA could generate 9 billion US$ in funds annually to incentivize clean alternative fuels and energy efficient vehicles, which could lower US dependency on foreign fuel sources. This policy is also credible from a sustainable development perspective than the alternative CO2 tax, since the high CO2 tax would have led to large-scale shifts in tank tourism – and bookkeeping GHG reductions for Switzerland – although the real reductions would have been less than half of the total effect and neighbouring countries would have been left with the excess emissions. Licensing and parking charges The most renowned area licensing and parking charges scheme has been applied in Singapore with effective reduction in total vehicular traffic and hence energy (petroleum) demand (Fwa, 2002). The area licensing scheme in Singapore resulted in 1.043 GJ per day energy savings with private vehicular traffic reducing by 75% (Fwa, 2002). Unfortunately there is currently a lack of data on potential GHG savings associated with policy, institutional and fiscal reforms/measures with respect to transport particularly in other developing countries. General estimates of reduction in use of private vehicle operators resulting from fuel pricing and taxing are 15–20% (World Bank, 2002; Martin et al., 1995).
Niederberger (2005) outlines a voluntary agreement with the Swiss government under which the oil industry took
Table 5.16: Potential energy and GHG savings from pricing, taxes and charges for road transport Tax/pricing measure
Potential energy/GHG savings or transport improvements
Reference
Optimal road pricing based on congestion charging (London, UK)
20% reduction in CO2 emissions as a result of 18% reduction in traffic
Transport for London (2005)
Congestion pricing of the Namsan Tunnels (Seoul, South Korea)
34% reduction of peak passenger traffic volume. Traffic flow from 20 to 30 km/hr.
World Bank (2002)
Fuel pricing and taxation
15-20% for vehicle operators.
Martin et al. (1995)
Area Licensing Scheme (Singapore)
1.043 GJ/day energy savings. Vehicular traffic reduced by 50%. Private traffic reduced by 75%. Travel speed increased 20 to 33 km/hr.
Fwa (2002)
Urban gasoline tax (Canada)
1.4 Mton by 2010 2.6 Mton by 2020
Transportation in Canada; www.tc.gc. ca/pol/en/Report/anre1999/tc9905be.htm
Congestion charge trial in Stockholm (20052006)
13% reduction of CO2
http://www.stockholmsforsoket.se/ templates/page.aspx?id=2453
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Box 5.7 Policies to promote biofuels Policies to promote biofuels are prominent in national emissions abatement strategies. Since benefits of biofuels for CO2 mitigation mainly come from the well-to-tank part, incentives for biofuels are more effective climate policies if they are tied to the whole well-to-wheels CO2 efficiencies. Thus preferential tax rates, subsi-dies and quotas for fuel blending should be calibrated to the benefits in terms of net CO2 savings over the whole well-to-wheel cycle associated with each fuel. Development of an index of CO2 savings by fuel type would be useful and if agreed internationally could help to liberalise markets for new fuels. Indexing incentives would also help to avoid discrimination between feedstocks. Subsidies that support production of specific crops risk being counterproductive to emission policies in the long run (ECMT, 2007). In order to avoid negative effects of biofuel production on sustainable development (e.g. biodiversity impacts), additional conditions could be tied to incentives for biofuels. The following incentives for biofuels are implemented or in the policy pipeline (Hamelinck, et al. 2005): Brazil was one of the first countries to implement policies to stimulate biofuel consumption. Currently, flexible fuel vehicles are eligible for federal value-added tax reductions ranging from 15–28%. In addition, all gasoline should meet a legal alcohol content requirement of 20–24%. Motivated by the biofuels directive in the European Union, the EU member states have implemented a variety of policies. Most of the member states have implemented an excise duty relief. Austria, Spain, Sweden, the Netherlands and the UK have implemented an obligation or intend to implement an obligation in the coming years. Sweden and Austria also implemented a CO2 tax. The American Jobs creation act of 2004 provides tax incentives for alcohol and biodiesel fuels. The credits have been set at 0.5–1 US$/gallon (about 0.11–0.21 €/litre). Some 39 states have developed additional policy programmes or mechanisms to support the increase use of biofuel. The types of measures range from tax exemptions on resources required to manufacturing or distributing biofuels (e.g. labour, buildings); have obligatory targets for governmental fleets and provide tax exemptions or subsidies when purchasing more flexible vehicles. One estimate is that total subsidies in the US for biofuels were 5.1–6.8 billion US$ in 2006, about half in the form of fuel excise tax reductions, and another substantial amount for growing corn used for ethanol. New blending mandates have also appeared in China, Canada, Colombia, Malaysia and Thailand. Four provinces in China added dates for blending in major cities, bringing to nine the number of provinces with blending mandates (REN21, 2006).
5.5.1.3
Regulatory and operational measures
Although pricing and fiscal instruments are obvious tools for government policy, they are often not very effective, as reflected by the potential reduction in fuel savings (IEA, 2003). Potential effective (and cost-effective) non-fiscal measures that can be effective in an oil crisis are regulatory measures such as: • Lower speed limits on motorways; • High occupancy vehicle requirements for certain roads and networks; • Vehicle maintenance requirements; • Odd/even number plate and other driving restrictions; • Providing information on CO2 emission performances of vehicles (labelling); • Establishing carbon standards for fuels; • Direct traffic restrictions (e.g., no entry into business district); • Free/expanded urban public transport; • Encouraging alternatives to travel (e.g., greater telecommuting); • Emergency switching from road to rail freight; • Reducing congestion through removal of night-time/ weekend driving bans for freight.
IEA (2003) indicates that such measures could contribute to significant oil savings. This is a typical case where a portfolio of measures is applied together and they would work well with adequate systems of monitoring and enforcement. For the measures to be implemented effectively considerable preparatory work is necessary and Table 5.17 shows examples of what could be done to ensure the measures proposed above can be effective in oil savings. The combined effect of these regulatory measures used to target light-duty vehicles (in addition to blending non-petroleum fuels with gasoline and diesel) is estimated to be a reduction of 15% of daily fuel consumption. In OECD countries vehicles consume 10–20% more fuel per km than indicated by their rated efficiency. It is estimated that 5–10% reduction in fuel consumption can be achieved by stronger inspection and vehicle maintenance programmes, adoption of on board technologies, more widespread driver training and better enforcement and control of vehicle speeds.
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Table 5.17: Preparations required to implement some regulatory measures Measure to be implemented
Preparatory work
Speed limitsa)
• •
Install electronic speed limit system Change the law
Carpool days
• • •
System of finding rides Car parks High occupancy car lanes
Energy efficient car and • driving choice from home • •
On board efficient indicator systems Driver training Information on efficient car purchases
Telecommuting days
Telecommuting programmes and protocols Practice
• •
Clean car choice
• •
Car free days
• •
Public awareness of car consumption Labeling based on CO2 performance Biking/walking/transit facilities Home/job commuting reduced
a) The Swedish road administration has calculated the effect of regulatory measures on speed. Exceeding speed limits on the Swedish road network gives an extra CO2 emission of 0.7Mt on an annual basis (compared to total emissions of 20 Mt). A large part of this can be tackled using speed cameras and in the future intelligent speed adaptation in vehicles. Besides this, reduction of speed limits (by 10 km/h except for the least densely populated areas where there is no alternative to the private car) could result in a similar amount of CO2 reduction. Source: Adapted from IEA, 2003.
Vehicle travel demand can be reduced by 10–15% by aggressively combining infrastructure improvements, intelligent transport technologies and systems (e.g., better routing systems and congestion reduction), information systems and better transit systems in addition to road pricing. Another regulatory approach, under consideration in California as part of its 2006 Global Warming Solutions Act, is carbon-based fuel standards. Fuel suppliers would be required to reduce the carbon content of their fuels according to a tightening schedule. For instance, gasoline from conventional oil would be rated at 1.0, ethanol from corn and natural gas at 0.8, electricity for vehicles at 0.6 and so on. The fuel suppliers would be allowed to trade and bank credits and car makers would be required to produce vehicles at an amount that corresponds to the planned sales of alternative fuels. Reductions of 5% or more in transport fuel GHGs by 2020 are envisioned, with much greater reductions in later years. 5.5.1.4
Fuel economy standards – road transport
Most industrialized nations now impose fuel economy requirements (or their equivalent in CO2 emissions requirements)
on new light-duty vehicles (Plotkin, 2004; An and Sauer, 2004). The first standards were imposed by the United States in 1975, requiring 27.5 mpg (8.55 L/100 km) corporate fleet averages for new passenger cars and 20.7 mpg (11.36 L/100 km) for light trucks (based on tests instituted by the US Environmental Protection Agency, using the ‘CAFE’ driving cycle) by 1985. The passenger car standard remains unchanged, whereas the light truck standard has recently been increased to 22.2 mpg (10.6 L/100 km) for the 2007 model year and to 23.5 mpg (10.0 L/100 km) in model year 2010.40 Additional standards (some voluntary) include: • European Union: a 2008 fleet wide requirement41 of 140 gCO2/km, about 41 mpg (5.74 L/100 km) of gasoline equivalent, using the New European Driving Cycle (NEDC), based on a Voluntary Agreement between the EU and the European manufacturers, with the Korean and Japanese manufacturers following in 2009. Recent slowing of the rate of efficiency improvement has raised doubts that the manufacturers will achieve the 2008 and 2009 targets (Kageson, 2005). • Japan: a 2010 target of about 35.5 mpg (6.6 L/100 km) for new gasoline passenger vehicles, using the Japan 10/15 driving cycle based on weight-class standards. • China: weight-class standards that are applied to each new vehicle using the NEDC driving cycle, with target years of 2005 and 2008. At the historical mix of vehicles, the standards are equivalent to fleet targets of about 30.4 mpg (7.7 L/100 km) by 2005 and 32.5 mpg (7.2 L/100 km) by 2008 (An and Sauer, 2004). • Australia: a 2010 target for new vehicles of 18% reduction in average fuel consumption relative to the 2002 passenger car fleet, corresponding to 6.8 L/100 km, or 34.6 mpg. (DfT, 2003), based on a voluntary agreement between industry and government. • The State of California has established GHG emission standards for new light-duty vehicles designed to reduce per-vehicle emissions by 22% in 2012 and 30% by 2016. Several US states have decided to adopt these standards, as well. At the time of writing, US industry and the federal government were fighting these standards in the courts. The NEDC and Japan 10/15 driving cycles are slower than the US CAFE cycle and, for most vehicles (though probably not for hybrids), will yield lower measured fuel economy levels than the CAFE cycle for the same vehicles. Consequently, if they reach their targets, the EU, Japanese and Chinese fleets are likely to achieve fuel economies higher than implied by the values above if measured on the US test. A suggested correction factor (for the undiscounted test results) is 1.13 for the EU and China and 1.35 for Japan (An and Sauer, 2004), though these are likely to be at the high end of the possible range of values
40 In 2011, manufacturers must comply with a reformed system where required CAFE levels depend on the manufacturer’s fleet mix based on vehicle “footprint,” or track width wheelbase (NHTSA CAFE website, 2006). 41 There are no specific corporate requirements for the entire new light-duty vehicle fleet.
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55
miles / gallon
liter / 100 km
4.3
EU
50
4.7 Japan
45
5.2
40
5.9 China
35
6.7
Australia Canada
California 7.8
30
25
2002
9.4
US
2004
2006
2008
2010
2012
2014
2016
Figure 5.18: Fuel economy and GHG emission standards Note: all the fuel economy targets represent test values based on artificial driving cycles. The standards in the EU and Australia are based on voluntary agreements. In most cases, actual on-road fuel economy values will be lower; for example, the US publishes fuel economy estimates for individual LDVs that are about 15% lower than the test val-ues and even these values appear to be optimistic. Miles/gallon is per US gallon.
for such factors.42 Figure 5.18 shows the ‘corrected’ comparison of standards. Recent studies of the costs and fuel savings potential of technology improvements indicate considerable opportunity to achieve further fleet fuel economy gains from more stringent standards. For example, the US National Research Council (NRC, 2002) estimates that US light-duty vehicle fuel economy can be increased by 25–33% within 15 years with existing technologies that cost less than the value of fuel saved. A study by Ricardo Consulting Engineers for the UK Department for Transport (Owen and Gordon, 2002) develops a step-wise series of improvements in a baseline diesel passenger car that yields a 38% reduction in CO2 emissions (a 61% increase in fuel economy), to 92 g/km, by 2013 using parallel hybrid technology at an incremental cost of 2300–3,100 £ (4200–5700 US$) with a 15,300 £ (28,000 US$) baseline vehicle. Even where fuel savings will outweigh the cost of new technologies, however, the market will not necessarily adopt these technologies by itself (or achieve the maximum fuel economy benefits from the technologies even if they are adopted). Two crucial deterrents are, first, that the buyers of new vehicles tend to consider only the first three years or so of fuel savings (NRC, 2002; Annema et al., 2001), and second, that vehicle buyers will take some
of the benefits of the technologies in higher power and greater size rather than in improved fuel economy. Further, potential benefits for consumers over the vehicle’s lifetime are generally small, while risks for producers are high (Greene, 2005). Also, neither the purchasers of new vehicles nor their manufacturers will take into account the climate effects of the vehicles. Strong criticisms have been raised about fuel economy standards, particularly concerning claimed adverse safety implications of weight reductions supposedly demanded by higher standards and increased driving caused by the lower fuel costs (per mile or km) associated with higher fuel economy. The safety debate is complex and not easily summarized. Although there is no doubt that adding weight to a vehicle improves its safety in some types of crashes, it does so at the expense of other vehicles; further, heavy light trucks have been shown to be no safer, and in some cases less safe than lighter passenger cars, primarily because of their high rollover risk (Ross et al., 2006). The US National Highway Traffic Safety Administration (NHTSA) has claimed that fleet wide weight reductions ‘reduce’ fleet safety (Kahane, 2003), but this conclusion is strongly disputed (DRI, 2004; NRC, 2002). An important concern with the NHTSA analysis is that it does not
42 These values are derived by simulating US vehicles running on the CAFE, NEDC, and Japan 10.15 cycles and comparing their estimated fuel economies. Because car manufacturers design their vehicles to do well on the cycles on which they will be tested, the US vehicles are likely to do a bit worse on the NEDC and Japan 10.15 cycles than they would have had they been designed for those cycles. This will somewhat exaggerate the estimated differences between the cycles in their effects on fuel economy.
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separate the effects of vehicle weight and size. In any case, other factors, e.g., overall vehicle design and safety equipment, driver characteristics, road design, speed limits and alcohol regulation and enforcement play a more significant role in vehicle safety than does average weight. Some have argued that increases in driving associated with reduced fuel cost per mile will nullify the benefits of fuel economy regulations. Increased driving ‘is’ likely, but it will be modest and decline with higher income and increased motorization. Recent data implies that a driving ‘rebound’ would reduce the GHG reduction (and reduce oil consumption) benefits from higher standards by about 10% in the United States (Small and Van Dender, 2007) but more than this in less wealthy and less motorized countries.
•
•
In deciding to institute a new fuel economy standard, governments should consider the following: • Basing stringency decisions on existing standards elsewhere requires careful consideration of differences between the home market and compared markets in fuel quality and availability; fuel economy testing methods; types and sizes of vehicles sold; road conditions that may affect the robustness of key technologies; and conditions that may affect the availability of technologies, for example, availability of sophisticated repair facilities. • There are a number of different approaches to selecting stringency levels for new standards. Japan selected its weight class standards by examining ‘top runners’ – exemplary vehicles in each weight class that could serve as viable targets for future fleet wide improvements. Another approach is to examine the costs and fuel saving effects of packages of available technologies on several typical vehicles, applying the results to the new vehicle fleet (NRC, 2002). Other analyses have derived cost curves (percent increase in fuel economy compared with technology cost) for available technology and applied these to corporate or national fleets (Plotkin et al., 2002). These approaches are not technology-forcing, since they focus on technologies that have already entered the fleet in mass-market form. More ambitious standards could demand the introduction of emerging technologies. Selection of the appropriate level of stringency depends, of course, on national goals and concerns. Further, the selection of enforcement deadlines should account for limitations on the speed with which vehicle manufacturers can redesign multiple models and introduce the new models on a schedule that avoids severe economic disruption. • The structure of the standard is as important as its level of stringency. Basing target fuel economy on vehicle weight (Japan, China) or engine size (Taiwan, South Korea) will tend to even out the degree of difficulty the standards impose on competing automakers, but will reduce the potential fuel economy gains that can be expected (because weight-based standards eliminate weight reduction and engine-size-based standards eliminate engine downsizing as viable means of 374
achieving the standards). Basing the standard on vehicle wheelbase times track width may provide safety benefits by providing a positive incentive to maintain or increase these attributes. Using a uniform standard for all vehicles or for large classes of vehicles (as in the US) is simple and easy to explain, but creates quite different challenges on different manufacturers depending on the market segments they focus on. Allowing trading of fuel economy ‘credits’ among different vehicles or vehicle categories in an automaker’s fleet, or even among competing automakers, will reduce the overall cost of standards without reducing the total societal benefits, but may incur political costs from accusations of allowing companies or individuals to ‘buy their way out’ of efficiency requirements. Alternatives (or additions) to standards are worth investigating. For example, ‘feebates’, which award cash rebates to new vehicles whose fuel economy is above a designated level (often the fleet average) and charge a fee to vehicles with lower fuel economy, may be an effective market-based measure to increase fleet fuel economy. An important advantage of feebates is that they provide a ‘continuous’ incentive to improve fuel economy, because an automaker can always gain a market advantage by introducing vehicles that are more efficient than the current average.
5.5.1.5
Transport Demand Management
Transport Demand Management (TDM) is a formal designation for programmes in many countries that improve performance of roads by reducing traffic volumes (Litman, 2003). There are many potential TDM strategies in these programmes with a variety of impacts. Some improve transport diversity (the travel options available to users). Others provide incentives for users to reduce driving, changing the frequency, mode, destination, route or timing of their travel. Some reduce the need for physical travel through mobility substitutes or more efficient land use. Some involve policy reforms to correct current distortions in transport planning practices. TDM is particularly appropriate in developing country cities, because of its low costs, multiple benefits and potential to redirect the motorization process. In many cases, effective TDM during early stages of development can avoid problems that would result if communities become too automobile dependent. This can help support a developing country’s economic, social and environmental objectives (Gwilliam et al., 2004). The set of strategies to be implemented will vary depending on each country’s demographic, geographic and political conditions. TDM strategies can have cumulative and synergetic impacts, so it is important to evaluate a set of TDM programmes as a package, rather than as an individual programme. Effective strategies usually include a combination of positive incentives to use alternative modes (‘carrots’ or ‘sweeteners’) and negative incentives to discourage driving (‘sticks’ or ‘levellers’). Recent
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literature gives a comprehensive overview of these programmes with several case studies (May et al., 2003; Litman, 2003; WCTRS and IPTS, 2004). Some major strategies such as pricing and land-use planning are addressed above. Below is a selective review of additional TDM strategies with significant potential to reduce vehicle travel and GHGs. Employer travel reduction strategies gained prominence from a late 1980s regulation in southern California that required employers with 100 or more employees to adopt incentives and rules to reduce the number of car trips by employees commuting to work (Giuliano et al., 1993). The State of Washington in the USA kept a state law requiring travel plans in its most urban areas for employers with 100 or more staff. The law reduced the percentage of employees in the targeted organizations who drove to work from 72–68% and affected about 12% of all trips made in the area. In the Netherlands, the reduction in single occupant commute trips from a travel plan averaged 5–15%. In the UK, in very broad terms, the average effectiveness of UK travel plans might be 6% in trips by drive alone to work and 0.74% in the total vehicle-km travelled to work by car. The overall effectiveness was critically dependent on both individual effectiveness and levels of plan take-up (Rye, 2002). Parking supply for employees is so expensive that employers naturally have an incentive to reduce parking demand. The literature found the price elasticity of parking demand for commuting at –0.31 to –0.58 (Deuker et al., 1998) and –0.3 (Veca and Kuzmyak, 2005) based on a non-zero initial parking price. The State of California enacted legislation that required employers with 50 or more persons who provided parking subsidies to offer employees the option to choose cash in lieu of a leased parking space, in a so-called parking cash-out programme. In eight case studies of employers who complied with the cash-out programme, the solo driver share fell from 76% before cashing out to 63% after cashing out, leading to the reduction in vehicle-km for commuting by 12%. If all the commuters who park free in easily cashed-out parking spaces were offered the cash option in the USA, it would reduce vehicle-km travelled per year by 6.3 billion (Shoup, 1997). Reducing car travel or CO2 emissions by substituting telecommuting for actual commuting has often been cited in the literature, but the empirical results are limited. In the USA, a micro-scale study estimated that 1.5% of the total workforce telecommuted on any day, eliminating at most 1% of total household vehicle-km travelled (Mokhtarian, 1998), while a macro-scale study suggested that telecommuting reduced annual vehicle-km by 0–2% (Choo et al., 2005). Reduction of CO2 emissions by hard measures, such as car restraint, often faces public opposition even when the proposed measures prove effective. Soft measures, such as a provision of information and use of communication strategies and educational techniques (OECD, 2004a) can be used for supporting the promotion of hard measures. Soft measures can also be directly
Transport and its infrastructure
helpful in encouraging a change in personal behaviour leading to an efficient driving style and reduction in the use of the car (Jones, 2004). Well organized soft measures were found to be effective for reducing car travel while maintaining a low cost. Following travel awareness campaigns in the UK, the concept of Individualized marketing, a programme based on a targeted, personalized, customized marketing approach, was developed and applied in several cities for reducing the use of the car. The programme reduced car trips by 14% in an Australian city, 12% in a German city and 13% in a Swedish city. The Travel Blending technique was a similar programme based on four special kits for giving travel-feedback to the participants. This programme reduced vehicle-km travelled by 11% in an Australian city. The monitoring study after the programme implementation in Australian cities also showed that the reduction in car travel was maintained (Brog et al., 2004; Taylor and Ampt, 2003). Japanese cases of travel-feedback programmes supported the effectiveness of soft measures for reducing car travel. The summary of the travel-feedback programmes in residential areas, workplaces and schools indicated that car use was reduced by 12% and CO2 emissions by 19%. It also implied that the travel-feedback programmes with a behavioural plan requiring a participant to make a plan for a change showed better results than programmes without one (Fujii and Taniguchi, 2005). 5.5.2
Aviation and shipping
In order to reduce emissions from air and marine transport resulting from the combustion of bunker fuels, new policy frameworks need to be developed. Both the ICAO and IMO have studied options for limiting GHG emissions. However, neither has as yet been able to devise a suitable framework for implementing effective mitigation policies. 5.5.2.1
Aviation
IPCC (1999), ICAO/FESG (2004a,b), Wit et al. (2002 and 2005), Cames and Deuber (2004), Arthur Andersen (2001) and others have examined potential economic instruments for mitigating climate effects from aviation. At the global level no support exists for the introduction of kerosene taxes. The ICAO policy on exemption of aviation fuel from taxation has been called into question mainly in European states that impose taxes on fuel used by other transport modes and other sources of GHGs. A study by Resource Analysis (1999) shows that introducing a charge or tax on aviation fuel at a ‘regional’ level for international flights would give rise to considerable distortions in competition and may need amendment of bilateral air service agreements. In addition, the effectiveness of a kerosene tax imposed on a regional scale would be reduced as airlines could take ‘untaxed’ fuel onboard into the taxed area (the so-called tankering effect). Wit and Dings (2002) analyzed the economic and environmental impacts of en-route emission charges for all 375
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flights in European airspace. Using a scenario-based approach and an assumed charge level of 50 US$/tCO2, the study found a cut in forecast aviation CO2 emissions in EU airspace of about 11 Mt (9%) in 2010. This result would accrue partly (50%) from technical and operational measures by airlines and partly from reduced air transport demand. The study found also that an en-route emission charge in European airspace designed in a non-discriminative manner would have no significant impact on competition between European and non-European carriers. In a study prepared for CAEP/6, the Forecasting and Economic Analysis Support Group (ICAO/FESG, 2004a) considered the potential economic and environmental impacts of various charges and emission trading schemes. For the period 1998–2010, the effects of a global CO2 charge with a levy equivalent to 0.02 US$/kg to 0.50 US$/kg jet fuel show a reduction in global CO2 emissions of 1–18%. This effect is mainly caused by demand effects (75%). The AERO modelling system was used to conduct the analyses (Pulles, 2002). As part of the analysis of open emission trading systems for CAEP/6, an impact assessment was made of different emission trading systems identified in ICF et al. (2004). The ICAO/FESG report (2004b) showed that under a Cap-and-Trade system for aviation, total air transport demand will be reduced by about 1% compared to a base case scenario (FESG2010). In this calculation, a 2010 target of 95% of the 1990-level was assumed for aviation on routes from and to Annex-I countries and the more developed non-Annex-I countries such as China, Hong Kong, Thailand, Singapore, Korea and Brazil. Furthermore a permit price of 20 US$/tCO2 was assumed. Given the relative high abatement costs in the aviation sector, this scenario would imply that the aviation sector would buy permits from other sectors for about 3.3 billion US$. In view of the difficulty of reaching global consensus on mitigation policies to reduce GHG emissions from international aviation, the European Commission decided to prepare climate policies for aviation. On 20 December 2006 the European Commission presented a legislative proposal that brings aviation emissions into the existing EU Emissions Trading Scheme (EU ETS). The proposed directive will cover emissions from flights within the EU from 2011 and all flights to and from EU airports from 2012. Both EU and foreign aircraft operators would be covered. The environmental impact of the proposal may be significant because aviation emissions, which are currently growing rapidly, will be capped at their average level in 2004– 2006. By 2020 it is estimated by model analysis that a total of 183 MtCO2 will be reduced per year on the flights covered, a 46% reduction compared with business-as-usual. However, aviation reduces the bulk of this amount through purchasing allowances from other sectors and through additional supply of Joint Implementation and Clean Development Mechanism credits. In 2020 aviation reduces its own emissions by 3% below business-as-usual (EC, 2006).
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If emission trading or emission charges were applied to the aviation sector in isolation, the two instruments would in principle be equivalent in terms of cost-effectiveness. However, combining the reduction target for aviation with the emission trading scheme of other sectors increases overall economic efficiency by allowing the same amount of reductions to be made at a lower overall cost to society. Therefore, if aviation were to achieve the same environmental goal under emission trading and emission charges, the economic costs for the sector and for the economy as a whole would be lower if this was done under an emission trading scheme including other sectors rather than under a charging system for aviation only. Alternative policy instruments that may be considered are voluntary measures or fuel taxation for domestic flights. Fuel for domestic flights, which are less vulnerable to economic distortions, is already taxed in countries such as the USA, Japan, India and the Netherlands. In parallel to the introduction of economic instruments such as emission trading, governments could improve air traffic management. Policies to address the full climate impact of aviation A major difficulty in developing a mitigation policy for the climate impacts of aviation is how to cover non-CO2 climate impacts, such as the emission of nitrogen oxides (NOx) and the formation of condensation trails and cirrus clouds (see also Box 5.1 in section 5.2). IPCC (1999) estimated these effects to be about 2 to 4 times greater than those of CO2 alone, even without considering the potential impact of cirrus cloud enhancement. This means that the perceived environmental effectiveness of any mitigation policy will depend on the extent to which these non-CO2 climate effects are also taken into account. Different approaches may be considered to account for nonCO2 climate impacts from aviation (Wit et al., 2005). A first possible approach is where initially only CO2 from aviation is included in for example an emission trading system, but flanking instruments are implemented in parallel such as differentiation of airport charges according to NOx emissions. Another possible approach is, in case of emission trading for aviation, a requirement to surrender a number of emission permits corresponding to its CO2 emissions multiplied by a precautionary average factor reflecting the climate impacts of non-CO2 impacts. It should be emphasised that the metric that is a suitable candidate for incorporating the non-CO2 climate impacts of aviation in a single metric that can be used as a multiplier requires further development, being fairly theoretical at present. The feasibility of arriving at operational methodologies for addressing the full climate impact of aviation depends not only on improving scientific understanding of non-CO2 impacts, but also on the potential for measuring or calculating these impacts on individual flights.
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5.5.2.2
Transport and its infrastructure
Shipping
CO2 emission indexing scheme The International Maritime Organisation (IMO), a specialized UN agency, has adopted a strategy with regard to policies and measures, focusing mainly on further development of a CO2 emission indexing scheme for ships and further evaluation of technical, operational and market-based solutions. The basic idea behind a CO2 emission index is that it describes the CO2 efficiency (i.e., the fuel efficiency) of a ship, i.e., the CO2 emission per tonne cargo per nautical mile. This index could, in the future, assess both the technical features (e.g., hull design) and operational features of the ship (e.g., speed). In June 2005, at the 53rd session of the Marine Environment Protection Committee of IMO (IMO, 2005), interim guidelines for voluntary ship CO2 emission indexing for use in trials were approved. The Interim Guidelines should be used to establish a common approach for trials on voluntary CO2 emission indexing, which enable shipowners to evaluate the performance of their fleet with regard to CO2 emissions. The indexing scheme will also provide useful information on a ship’s performance with regard to fuel efficiency and may thus be used for benchmarking purposes. The interim guidelines will later be updated, taking into account experience from new trials as reported by industry, organisations and administrations. A number of hurdles have to be overcome before such a system could become operational. The main bottleneck appears to be that there is major variation in the fuel efficiency of similar ships, which is not yet well understood (Wit et al., 2004). This is illustrated by research by the German delegation of IMO’s Working Group on GHG emission reduction (IMO, 2004), in which the specific energy efficiency (i.e., a CO2 emission index) was calculated for a range of container ships, taking into account engine design factors rather than operational data. The results of this study show that there is considerable scatter in the specific engine efficiency of the ships investigated, which could not be properly explained by the deadweight of the ships, year of build, ship speed and several other ship design characteristics. The paper therefore concludes that the design of any CO2 indexing scheme and its differentiation according to ship type and characteristics, requires in-depth investigation. Before such a system can be used in an incentive scheme, the reasons for the data scatter need to be understood. This is a prerequisite for reliable prediction of the economic, competitive and environmental effects of any incentive based on this method. Voluntary use and reporting results of CO2 emission indexing may not directly result in GHG emission reductions, although it may well raise awareness and trigger certain initial moves towards ‘self regulation’. It might also be a first step
in the process of designing and implementing some of the other policy options. Reporting of the results of CO2 emission indexing could thus generate a significant impetus to the further development and implementation of this index, since it would lead to widespread experience with the CO2 indexing methodology, including reporting procedure and monitoring, for shipping companies as well as for administrations of states. In the longer term, in order to be more effective, governments may consider using CO2 indexing via the following paths: 1. The indexing of ship operational performance is introduced as a voluntary measure and over time developed and adopted as a standard; 2. Based on the experience with the standard, it will act as a new functional requirement when new buildings are ordered, hence over time the operational index will affect the requirements from ship owners related to the energy efficiency of new ships; 3. Differentiation of en route emission charges or existing port dues on the basis of a CO2 index performance; 4. To use the CO2 index of specific ship categories as a baseline in a (voluntary) baseline-and-credit programme. Economic instruments for international shipping There are currently only a few cases of countries or ports introducing economic instruments to create incentives to reduce shipping emissions. Examples include environmentally differentiated fairway dues in Sweden, the Green Award scheme43 in place in 35 ports around the world, the Green Shipping bonus in Hamburg and environmental differentiation of tonnage tax in Norway. None of these incentives are based on GHG emissions, but generally relate to fuel sulphur content, engine emissions (mainly NOx), ship safety features and management quality. Harrison et al. (2004) explored the feasibility of a broad range of market-based approaches to regulate atmospheric emissions from seagoing ship in EU sea areas. The study focused primarily on policies to reduce the air pollutants SO2 and NOx, but the approaches adopted may to a certain extent also be applicable to other emissions, including CO2. According to a follow-up study by Harrison et al. (2005) the main obstacles to a programme of voluntary port dues differentiation are to provide an adequate level of incentive, alleviating ports’ competitive concerns and reconciling differentiation with specially negotiated charges. Swedish experience suggests that when combined with a centrally determined mandatory charging programme, these problems may be surmountable. However, in many cases a voluntary system would not likely be viable and other approaches to emissions reductions may therefore be required. An alternative economic instrument, such as a fuel tax is vulnerable to evasion; that is ships may avoid the tax by taking
43 www.greenaward.org
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fuel on board outside the taxed area. Offshore bunker supply is already common practice to avoid paying port fees or being constrained by loading limits in ports. Thus even a global fuel tax could be hard to implement to avoid evasion, as an authority at the port state level would have to collect the tax (ECON, 2003). A CO2-based route charge or a (global) sectoral emission trading scheme would overcome this problem if monitoring is based on the carbon content of actual fuel consumption on a single journey. As yet there is no international literature that analyzes the latter two policy options. Governments may therefore consider investigating the feasibility and effectiveness of emission charges and emission trading as policy instruments to reduce GHG emissions from international shipping. 5.5.3
Non-climate policies
Climate change is a minor factor in decision making and policy in the transport sector in most countries. Policies and measures are often primarily intended to achieve energy security and/or sustainable development benefits that include improvements in air pollution, congestion, access to transport facilities and recovery of expenditure on infrastructure development. Achieving GHG reduction is therefore often seen as a co-benefit of policies and measures intended for sustainable transport in the countries. On the other hand, there are many transport policies that lead to an increase in GHG emissions. Depending on their orientation, transport subsidies can do both. The impact of transport subsidies Globally, transport subsidies are significant in economic terms. Van Beers and Van den Bergh (2001) estimated that in the mid-1990s transport subsidies amounted to 225 billion US$, or approximately 0.85% of the world GDP. They estimated that transport subsidies affect over 40% of world trade. In a competitive environment (not necessarily under full competition), subsidies decrease the price of transport. This results in the use of transport above its equilibrium value and most of the time also results in higher emissions, although this depends on the type of subsidy. Secondly, they decrease the incentive to economise on fuel, either by driving efficiently or by buying a fuel-efficient vehicle. A quantitative appraisal of the effect of subsidies on GHG emissions is very complicated (Nash et al., 2002). Not only have shifts between fuels and transport modes to be taken into account, but the relation between transport and the production structure also needs to be analysed. As a result, reliable quantitative assessments are almost non-existent (OECD, 2004a). Qualitative appraisals are less problematic. Transport subsidies that definitely raise the level of GHG emissions include subsidies on fossil transport fuels, subsidies on commuting and subsidies on infrastructure investments. Many, mostly oil producing, countries provide their inhabitants with transport fuels below the world price. Some 378
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countries spend more than 4% of their GDP on transport fuel subsidies (Esfahani, 2001). Many European countries and Japan have special fiscal arrangements for commuting expenses. In most of these countries, taxpayers can deduct real expenses or a fixed sum from their income (Bach, 2003). By reducing the incentive to move closer to work, these tax schemes enhance transport use and emissions. Not all transport subsidies result in higher emissions of GHGs. Some subsidies stimulate the use of climatefriendly fuels. In many countries, excise duty exemptions on compressed natural or petroleum gas and on biofuels exist (e.g., Riedy, 2003). If these subsidies result in a change in the fuel mix, without resulting in more transport movements, they may actually decrease emissions of GHGs. The most heavily subsidised form of transport is probably public transport, notably suburban and regional passenger rail services. In the USA, fares only cover 25% of the costs, in Europe 50% (Brueckner, 2004). Although public transport generally emits fewer GHGs per passenger-km, the net effect of these subsidies has not been quantified. It depends on the balance between increased GHG emissions due to higher demand (due to lower ‘subsidised’ fares) and substitution of relatively less efficient transport modes. 5.5.4
Co-benefits and ancillary benefits
The literature uses the term ancillary benefits when focusing primarily on one policy area, and recognizing there may be benefits with regard to other policy objectives. One speaks of co-benefits when looking from an integrated perspective. This section focuses on co-benefits and ancillary benefits of transport policies. Chapter 11.6 provides a general discussion of the benefits and linkages related to air pollution policies. As mentioned above, several different benefits can result from one particular policy. In the field of transport, local air pollutants and GHGs have a common source in motorized traffic, which may also induce congestion, noise and accidents. Addressing these problems simultaneously, if possible, offers the potential of large cost reductions, as well as reductions of health and ecosystems risks. A recent review of costs of road transport emissions, and particularly of particulates PM2.5, for European countries strongly supports that view (HEATCO, 2006). Tackling these problems would also contribute to more effective planning of transport, land use and environmental policy (UN, 2002; Stead et al., 2004). This suggests that it would be worthwhile to direct some research towards the linkages between these effects. Model studies indicate a potential saving of up to 40% of European air pollution control costs if the changes in the energy systems that are necessary for compliance with the Kyoto protocol were simultaneously implemented (Syri et al., 2001). For China, the costs of a 5–10% CO2 reduction
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% of direct transport benefits
40
20 Carbon credits Cost of illness health benefits
0
Total health benefits
-20
Downtown (toll:2US$)
AV ring AV ring (toll:2US$) (bus toll:4US$)
Figure 5.19: Co-benefits from different mitigation measures in Santiago de Chile Note: toll is applied for cars/busses to enter downtown area or inside the Americo Vespucio ring around the city. Source: Cifuentes and Jorquera, 2002.
would be compensated by increased health benefits from the accompanying reduction in particulate matter (Aunan et al., 1998). McKinley et al. (2003) analyzed several integrated environmental strategies for Mexico City. They conclude that measures to improve the efficiency of transport are the key to joint local/global air pollution control in Mexico City. The three measures in this category that were analyzed, taxi fleet renovation, metro expansion and hybrid buses, all have monetized public health benefits that are larger than their costs when the appropriate time horizon is considered. A simulation of freight traffic over the Belgian network indicated that a policy of internalizing the marginal social costs caused by freight transport types would induce a change in the modal shares of trucking, rail and inland waterways transport. Trucking would decrease by 26% and the congestion cost it created by 44%. It was estimated that the total cost of pollution and GHG emissions (together) would decrease by 15.4%, the losses from accidents diminish by 24%, the cost of noise by 20% and wear and tear by 27%. At the same time, the total energy consumption by the three modes would decrease by 21% (Beuthe et al., 2002). Other examples of worthwhile policies can be given. The policy of increasing trucks’ weight and best practices awareness in Sweden, UK and the Netherlands lead to a consolidation of loads that resulted in economic benefits as well as environmental benefits, including a decrease in CO2 emissions (MacKinnon, 2005; Leonardi and Baumgartner, 2004). Likewise, the Swiss heavy vehicle fee policy also leads to better loaded vehicles and a decrease of 7% in CO2 emissions (ARE, 2004a). Obviously, promotion of non-motorized transport (NMT) has the large and consistent co-benefits of GHG reduction, air quality and people health improvement (Mohan and Tiwari, 1999).
In the City of London a congestion charge was introduced in February 2003, to reduce congestion. Simultaneous with the introduction of the charge, investment in public transport increased to provide a good alternative. The charge is a fee for motorists driving into the central London area. It was introduced in February 2003. Initially set at 5 £/day (Monday to Friday, between 7 am and 6.30 pm), it was raised to 8 £ in July 2005. The charge will be extended to a larger area in 2007. On a costbenefit rating, the results of the charge are not altogether clear (Prud’homme and Bocarejo, 2005, Mackie, 2005). However, it contributed to a 30% decrease of the traffic by the chargeable vehicles in the area and less congestion, to higher speed of private vehicles (+20%) and buses (+7%), and to an increased use of public transport, plus more walking and bicycling. The charge has had substantial ancillary benefits with respect to air quality and climate policy. All the volume and substitution effects in the charging zone has led to an estimated reductions in CO2 emissions of 20%. Primary emissions of NOx and PM10 fell by 16% after one year of introduction (Transport for London, 2006). A variant of that scheme has been in operation since 1975 in Singapore with similar results; Stockholm is presently experimenting with such a system, Trondheim, Oslo and Durham are other examples. Under the Integrated Environmental Strategies Program of the US EPA, analysis of public health and environmental benefits of integrated strategies for GHG mitigation and local environmental improvement is supported and promoted in developing countries. A mix of measures for Chile has been proposed, aimed primarily at local air pollution abatement and energy saving. Measures in the transport sector (CNG buses, hybrid diesel-electric buses and taxi renovation) proved to provide little ancillary benefits in the field of climate policy, see Figure 5.19. Only congestion charges were expected to have substantial ancillary benefits for GHG reduction (Cifuentes et al., 2001, Cifuentes & Jorquera, 2002). While there are many synergies in emission controls for air pollution and climate change, there are also trade-offs. Diesel engines are generally more fuel-efficient than gasoline engines and thus have lower CO2 emissions, but increase particle emissions. Air quality driven measures, like obligatory particle matter (PM) and NOx filters and in-engine measures, do not result in higher fuel use if appropriate technologies are used, like Selective Catalytic Reduction (SCR)- NOx catalyst. 5.5.5
Sustainable Development impacts of mitigation options and considerations on the link of adaptation with mitigation.
Within the transport sector there are five mitigation options with a clear link between sustainable development, adaptation and mitigation. These areas are biofuels, energy efficient, public transport, non-motorised transport and urban planning. Implementing these options would generally have positive social, environmental and economic side effects. The economic 379
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effects of using bio-energy and encouraging public transport systems, however, need to be evaluated on a case-by-case basis. For transport there are no obvious links between mitigation and adaptation policies and the impact on GHG emissions due to adaptation is expected to be negligible. Mitigation and sustainable development is discussed from a much wider perspective, including the other sectors, in Chapter 12, Section 12.2.4.
5.6 Key uncertainties and gaps in knowledge Key uncertainties in assessment of mitigation potential in the transport sector through the year 2030 are: • World oil supply and its impact on prices and alternative transport fuels; • R&D outcomes in several areas, especially biomass fuel production technology and its sustainability if used on a massive scale, and batteries. These outcomes will strongly influence the future costs and performance of a wide range of transport technologies. The degree to which the potential can be realized will crucially depend on the priority that developed and developing countries give to GHG emissions mitigation. A key gap in knowledge is the lack of comprehensive and consistent assessments of the worldwide potential and cost to mitigate transport’s GHG emissions. There are also important gaps in basic statistics and information on transport energy consumption and GHG mitigation, especially in developing countries.
REFERENCES Abbot, C., 2002: Planning a Sustainable City: The Promise and Performance of Portland’s Urban Growth Boundary. In Urban Sprawl, G.D. Squires (ed.), The Urban Land Institute, pp. 207-235. ACEEE, 2001: Technical Options for Improving the Fuel Economy of U.S. Cars and Light Trucks by 2010-2015. DeCicco, J., F. An, and M. Ross, American Council for an Energy-Efficient Economy, <www. aceee.org/pubs/t012.htm> accessed 30/05/07. ADAC, 2005: Study on the effectiveness of Directive 1999/94/EC relating to the availability of consumer information on fuel economy and CO2 emissions in respect of the marketing of new passenger cars. München, March 2003. ADEME, 2006: Inventories of the worldwide fleets of refrigerating and air-conditioning equipment in order to determine refrigerant emissions: the 1990 to 2003 updating, ADEME, Paris. Airbus, 2004: Global Market Forecast 2004-2023. accessed 30/05/07. Akerman, J. and M. Hojer, 2006: How Much Transport Can the Climate Stand? - Sweden on a Sustainable Path in 2050. Energy Policy, 34, pp. 1944-1957.
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6 Residential and commercial1 buildings Coordinating Lead Authors: Mark Levine (USA), Diana Ürge-Vorsatz (Hungary)
Lead Authors: Kornelis Blok (The Netherlands), Luis Geng (Peru), Danny Harvey (Canada), Siwei Lang (China), Geoffrey Levermore (UK), Anthony Mongameli Mehlwana (South Africa), Sevastian Mirasgedis (Greece), Aleksandra Novikova (Russia), Jacques Rilling (France), Hiroshi Yoshino (Japan)
Contributing Authors: Paolo Bertoldi (Italy), Brenda Boardman (UK), Marilyn Brown (USA), Suzanne Joosen (The Netherlands), Phillipe Haves (USA), Jeff Harris (USA), Mithra Moezzi (USA)
Review Editors: Eberhard Jochem (Germany), Huaqing Xu (PR China)
This chapter should be cited as: Levine, M., D. Ürge-Vorsatz, K. Blok, L. Geng, D. Harvey, S. Lang, G. Levermore, A. Mongameli Mehlwana, S. Mirasgedis, A. Novikova, J. Rilling, H. Yoshino, 2007: Residential and commercial buildings. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
1
The category of non-residential buildings is referred to by different names in the literature, including commercial, tertiary, public, office, and municipal. In this chapter we consider all non-domestic residential buildings under the “commercial” sector.
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Table of Contents Executive Summary .................................................. 389 6.1
6.6
Introduction ...................................................... 391
6.6.1
Reduction in local/regional air pollution ............ 416
6.6.2
Improved health, quality of life and comfort ...... 416
6.6.3
Improved productivity ..................................... 417
6.6.4
Employment creation and new business opportunities ................................................... 417
GHG mitigation options in buildings and equipment ......................................................... 393
6.6.5
Improved social welfare and poverty alleviation 418
6.6.6
Energy security................................................ 418
6.4.1
Overview of energy efficiency principles ........... 394
6.6.7
Summary of co-benefits .................................. 418
6.4.2
Thermal envelope ............................................ 395
6.4.3
Heating systems.............................................. 396
6.4.4
Cooling and cooling loads ............................... 397
6.4.5
Heating, ventilation and air conditioning (HVAC) systems .......................................................... 399
6.4.6
Building energy management systems (BEMS) . 400
6.4.7
Active collection and transformation of solar energy ............................................................. 401
6.4.8
Domestic hot water ......................................... 402
6.4.9
Lighting systems ............................................. 402
6.2 Trends in buildings sector emissions .......... 391 6.3 6.4
Co-benefits of GHG mitigation in the residential and commercial sectors ............. 416
Scenarios of carbon emissions resulting from energy use in buildings ................................. 392
6.7
6.4.10 Daylighting ...................................................... 402 6.4.11 Household appliances, consumer electronics and office equipment ....................................... 403
Barriers to adopting building technologies and practices that reduce GHG emissions 418 6.7.1
Limitations of the traditional building design process and fragmented market structure ........ 418
6.7.2
Misplaced incentives ...................................... 419
6.7.3
Energy subsidies, non-payment and theft ........ 419
6.7.4
Regulatory barriers .......................................... 420
6.7.5
Small project size, transaction costs and perceived risk ................................................. 420
6.7.6
Imperfect information ...................................... 420
6.7.7
Culture, behaviour, lifestyle and the rebound effect .............................................................. 420
6.7.8
Other barriers .................................................. 421
6.4.12 Supermarket refrigeration systems ................... 404 6.4.13 Energy savings through retrofits ...................... 404
6.8
6.4.14 Trade-offs between embodied energy and operating energy ............................................. 405
Policies to promote GHG mitigation ...........in buildings ............................................................ 421 6.8.1
Policies and programmes aimed at building construction, retrofits, and installed equipment and systems .......................................................... 421
6.8.2
Policies and programmes aimed at appliances, lighting and office/consumer plug loads .......... 423
6.8.3
Cross-cutting policies and programmes that support energy efficiency and/or CO2 mitigation in buildings ..................................................... 425
6.8.4
Policies affecting non-CO2 gases ..................... 430
6.8.5
Policy options for GHG abatement in buildings: summary and conclusion ................................. 431
6.4.15 Trade-offs involving energy-related emissions and halocarbon emissions ...................................... 405 6.4.16 Summary of mitigation options in buildings ..... 406
6.5
Potential for and costs of greenhouse gas mitigation in buildings ................................... 409 6.5.1
Recent advances in potential estimations from around the world ............................................. 409
6.5.2
Recent advances in estimating the costs of GHG mitigation in buildings ...................................... 414
6.5.3
Supply curves of conserved carbon dioxide ..... 414
6.5.4
Most attractive measures in buildings .............. 415
6.5.5
Energy and cost savings through use of the Integrated Design Process (IDP)....................... 416
6.9
Interactions of mitigation options with vulnerability, adaptation and sustainable development ...................................................... 435 6.9.1
Interactions of mitigation options with vulnerability and adaptation ............................. 435
6.9.2
Synergies with sustainability in developing countries ........................................................ 436
6.10
Critical gaps in knowledge .......................... 437
References ................................................................... 437 388
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EXECUTIVE SUMMARY In 2004, emissions from the buildings sector including through electricity use were about 8.6 GtCO2, 0.1 GtCO2eq N2O, 0.4 GtCO2-eq CH4 and 1.5 GtCO2-eq halocarbons (including CFCs and HCFCs). Using an accounting system that attributes CO2 emissions to electricity supply rather than buildings end-uses, the direct energy-related carbon dioxide emissions of the building sector are about 3 Gt/yr. For the buildings sector the literature uses a variety of baselines. Therefore a baseline was derived for this sector based on the literature, resulting in emissions between the B2 and A1B SRES scenarios, with 11.1 Gt of emissions of CO2 in 2020 and 14.3 GtCO2 in 2030 (including electricity emissions but omitting halocarbons, which could conceivably be substantially phased out by 2030). Measures to reduce greenhouse gas (GHG) emissions from buildings fall into one of three categories: reducing energy consumption and embodied energy in buildings, switching to low-carbon fuels including a higher share of renewable energy, or controlling the emissions of non-CO2 GHG gases.2 This chapter devotes most attention to improving energy efficiency in new and existing buildings, which encompasses the most diverse, largest and most cost-effective mitigation opportunities in buildings. The key conclusion of the chapter is that substantial reductions in CO2 emissions from energy use in buildings can be achieved over the coming years using mature technologies for energy efficiency that already exist widely and that have been successfully used (high agreement, much evidence). A significant portion of these savings can be achieved in ways that reduce life-cycle costs, thus providing reductions in CO2 emissions that have a net benefit rather than cost. However, due to the long lifetime of buildings and their equipment, as well as the strong and numerous market barriers prevailing in this sector, many buildings do not apply these basic technologies to the level life-cycle cost minimisation would warrant (high agreement, much evidence). Our survey of the literature (80 studies) indicates that there is a global potential to reduce approximately 29% of the projected baseline emissions by 2020 cost-effectively in the residential and commercial sectors, the highest among all sectors studied in this report (high agreement, much evidence). Additionally at least 3% of baseline emissions can be avoided at costs up to 20 US$/tCO2 and 4% more if costs up to 100 US$/tCO2 are considered. However, due to the large opportunities at lowcosts, the high-cost potential has been assessed to a limited extent, and thus this figure is an underestimate (high agreement, much evidence). 2 3
Using the global baseline CO2 emission projections for buildings, these estimates represent a reduction of approximately 3.2, 3.6 and 4.0 GtCO2/yr in 2020, at zero, 20 US$/tCO2 and 100 US$/tCO2 respectively. Our extrapolation of the potentials to the year 2030 suggests that, globally, about 4.5, 5.0 and 5.6 GtCO2 at negative cost, <20 US$ and <100 US$/tCO2-eq respectively, can be reduced (approximately 30, 35 and 40% of the projected baseline emissions) (medium agreement, limited evidence). These numbers are associated with significantly lower levels of certainty than the 2020 ones due to very limited research available for 2030. While occupant behaviour, culture and consumer choice and use of technologies are also major determinants of energy use in buildings and play a fundamental role in determining CO2 emissions (high agreement, limited evidence), the potential reduction through non-technological options is rarely assessed and the potential leverage of policies over these is poorly understood. Due to the limited number of demand-side enduse efficiency options considered by the studies, the omission of non-technological options and the often significant cobenefits, as well as the exclusion of advanced integrated highly efficiency buildings, the real potential is likely to be higher (high agreement, limited evidence). There is a broad array of accessible and cost-effective technologies and know-how that have not as yet been widely adopted, which can abate GHG emissions in buildings to a significant extent. These include passive solar design, highefficiency lighting and appliances3, highly efficient ventilation and cooling systems, solar water heaters, insulation materials and techniques, high-reflectivity building materials and multiple glazing. The largest savings in energy use (75% or higher) occur for new buildings, through designing and operating buildings as complete systems. Realizing these savings requires an integrated design process involving architects, engineers, contractors and clients, with full consideration of opportunities for passively reducing building energy demands. Over the whole building stock the largest portion of carbon savings by 2030 is in retrofitting existing buildings and replacing energyusing equipment due to the slow turnover of the stock (high agreement, much evidence). Implementing carbon mitigation options in buildings is associated with a wide range of co-benefits. While financial assessment has been limited, it is estimated that their overall value may be higher than those of the energy savings benefits (medium agreement, limited evidence). Economic co-benefits include the creation of jobs and business opportunities, increased economic competitiveness and energy security. Other co-benefits include social welfare benefits for low-income households, increased access to energy services, improved indoor and outdoor air quality, as well as increased comfort,
Fuel switching is largely the province of Chapter 4, energy supply. By appliances, we mean all electricity-using devices, with the exception of equipment used for heating, cooling and lighting.
389
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health and quality of life. In developing countries, safe and highefficiency cooking devices and high-efficiency electric lighting would not only abate substantial GHG emissions, but would reduce mortality and morbidity due to indoor air pollution by millions of cases worldwide annually (high agreement, medium evidence). There are, however, substantial market barriers that need to be overcome and a faster pace of well-enforced policies and programmes pursued for energy efficiency and de-carbonisation to achieve the indicated high negative and low-cost mitigation potential. These barriers include high costs of gathering reliable information on energy efficiency measures, lack of proper incentives (e.g., between landlords who would pay for efficiency and tenants who realize the benefits), limitations in access to financing, subsidies on energy prices, as well as the fragmentation of the building industry and the design process into many professions, trades, work stages and industries. These barriers are especially strong and diverse in the residential and commercial sectors; therefore, overcoming them is only possible through a diverse portfolio of policy instruments (high agreement, medium evidence). Energy efficiency and utilisation of renewable energy in buildings offer a large portfolio of options where synergies between sustainable development and GHG abatement exist. The most relevant of these for the least developed countries are safe and efficient cooking stoves that, while cutting GHG emissions, significantly, reduce mortality and morbidity by reducing indoor air pollution. Such devices also reduce the
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workload for women and children and decrease the demands placed on scarce natural resources. Reduced energy payments resulting from energy-efficiency and utilisation of buildinglevel renewable energy resources improve social welfare and enhance access to energy services. A variety of government policies have been demonstrated to be successful in many countries in reducing energy-related CO2 emissions in buildings (high agreement, much evidence). Among these are continuously updated appliance standards and building energy codes and labelling, energy pricing measures and financial incentives, utility demand-side management programmes, public sector energy leadership programmes including procurement policies, education and training initiatives and the promotion of energy service companies. The greatest challenge is the development of effective strategies for retrofitting existing buildings due to their slow turnover. Since climate change literacy, awareness of technological, cultural and behavioural choices are important preconditions to fully operating policies, applying these policy approaches needs to go hand in hand with programmes that increase consumer access to information and awareness and knowledge through education. To sum up, while buildings offer the largest share of costeffective opportunities for GHG mitigation among the sectors examined in this report, achieving a lower carbon future will require very significant efforts to enhance programmes and policies for energy efficiency in buildings and low-carbon energy sources well beyond what is happening today.
Chapter 6
Residential and commercial buildings
6.1
Introduction
Measures to reduce greenhouse gas (GHG) emissions from buildings fall into one of three categories: reducing energy consumption4 and embodied energy in buildings, switching to low-carbon fuels including a higher share of renewable energy, or controlling the emissions of non-CO2 GHG gases. Renewable and low-carbon energy can be supplied to buildings or generated on-site by distributed generation technologies. Steps to decarbonise electricity generation can eliminate a substantial share of present emissions in buildings. Chapter 4 describes the options for centralized renewable energy generation, while this chapter covers building-level options for low-carbon electricity generation on-site. This chapter devotes most attention to energy efficiency in new and existing buildings, as fuel switching is largely covered elsewhere in this report (Chapter 4). NonCO2 GHGs are treated in depth in the IPCC special report on safeguarding the ozone layer and the climate system (IPCC/ TEAP, 2005), but some of the most significant issues related to buildings are discussed in this chapter as well. A very large number of technologies that are commercially available and tested in practice can substantially reduce energy use while providing the same services and often substantial co-benefits. After a review of recent trends in building energy use followed by a description of scenarios of energy use and associated GHG emissions, this chapter provides an overview of the various possibilities in buildings to reduce GHG emissions. Next, a selection of these technologies and practices is illustrated by a few examples, demonstrating the plethora of opportunities to achieve GHG emission reductions as significant as 70–80%. This is followed by a discussion of co-benefits from reducing GHG emissions from buildings, and a review of studies that have estimated the magnitude and costs of potential GHG reductions worldwide. In spite of the availability of these high-efficiency technologies and practices, energy use in buildings continues to be much higher than necessary. There are many reasons for this energy waste in buildings. The chapter continues with identifying the key barriers that prevent rational decision-making in energy-related choices affecting energy use in buildings. Countries throughout the world have applied a variety of policies in order to deal with these market imperfections. The following sections offer an insight into the experiences with the various policy instruments applied in buildings to cut GHG emissions worldwide. The past five years have shown increasing application of these policies in many countries in Europe and growing interest in several key developing and transition economies. In spite of this fact, global CO2 emissions resulting from energy use in buildings have increased at an average of 2.7% per year in the past five years for which data is available (1999–2004). The substantial barriers that need to be overcome and the relatively slow pace
4
of policies and programmes for energy efficiency will provide major challenges to rapid achievement of low-emission buildings.
6.2
Trends in buildings sector emissions
In 2004, direct emissions from the buildings sector (excluding the emissions from electricity use) were about 3 GtCO2, 0.4 GtCO2-eq CH4, 0.1 GtCO2-eq N2O and 1.5 GtCO2eq halocarbons (including CFCs and HCFCs). As mitigation in this sector includes a lot of measures aimed at electricity saving it is useful to compare the mitigation potential with carbon dioxide emissions, including those through the use of electricity. When including the emissions from electricity use, energy-related carbon dioxide emissions were 8.6 Gt/yr (Price et al., 2006), or almost a quarter of the global total carbon dioxide emissions as reported in Chapter 1. IEA estimates a somewhat higher fraction of carbon dioxide emissions due to buildings. Figure 6.1 shows the estimated emissions of CO2 from energy use in buildings from two different perspectives. The bar at the left represents emissions of CO2 from all energy end-uses in buildings. The bar at the right represents only those emissions from direct combustion of fossil fuels. Because the electricity can be derived from fuels with lower carbon content than current fuels, CO2 emissions from electricity use in buildings can also be altered on the supply side. Carbon dioxide emissions, including through the use of electricity in buildings, grew from 1971 to 2004 at an annual rate of 2%, – about equal to the overall growth rate
10
Gt CO2
8 emissions from electricity use and district heating in buildings
6
4 2 0 all energy sources
direct combustion in buildings
Figure 6.1: Carbon dioxide emissions from energy, 2004 Sources: IEA, 2006e and Price et al. 2006.
This counts all forms of energy use in buildings, including electricity.
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of CO2 emissions from all uses of energy. CO2 emissions for commercial buildings grew at 2.5% per year and at 1.7% per year for residential buildings during this period. The largest regional increases in CO2 emissions (including through the use of electricity) for commercial buildings were from developing Asia (30%), North America (29%) and OECD Pacific (18%). The largest regional increase in CO2 emissions for residential buildings was from Developing Asia accounting for 42% and Middle East/North Africa with 19%.
halocarbon (HFCs, CFCs and HCFCs) emissions, or 60% of the total halocarbon emissions was due to refrigerants and blowing agents for use in buildings (refrigerators, air conditioners and insulation) in 2002. Emissions due to these uses are projected to remain about constant until 2015 and decline if effective policies are pursued (IPCC/TEAP, 2005).
6.3 Scenarios of carbon emissions resulting from energy use in buildings
During the past seven years since the IPCC Third Assessment Report (TAR, IPCC, 2001), CO2 emissions (including through the use of electricity) in residential buildings have increased at a much slower rate than the 30-year trend (annual rate of 0.1% versus trend of 1.4%) and emissions associated with commercial buildings have grown at a faster rate (3.0% per year in last five years) than the 30-year trend (2.2%) (Price et al., 2006).
Figure 6.2 shows the results for the buildings sector of disaggregating two of the emissions scenarios produced for the IPCC Special Report on Emissions Scenarios (SRES) (IPCC, 2000), Scenarios A1B and B2, into ten world regions (Price et al., 2006). These scenarios show a range of projected buildings related CO2 emissions (including through the use of electricity): from 8.6 GtCO2 emissions in 2004 to 11.4 and 15.6 GtCO2 emissions in 2030 (B2 and A1B respectively), representing an approximately 30% share of total CO2 emissions in both scenarios. In Scenario B2, which has lower economic growth, especially in
Non-CO2 emissions (largely halocarbons, CFCs, and HCFCs, covered under the Montreal Protocol and HFCs) from cooling and refrigeration contribute more than 15% of the 8.6 GtCO2 emissions associated with buildings. About 1.5 GtCO2-eq of
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Figure 6.2: CO2 emissions including through the use of electricity: A1B (top) and B2 (bottom) IPCC (SRES) scenarios Note: Dark red – historic emissions 1971–2000 based on Price et al. (2006) modifications of IEA data. Light red – projections 2001–2030 data based on Price et al. (2006) disaggregation of SRES data; 2000–2010 data adjusted to actual 2000 carbon dioxide emissions. EECCA = Countries of Eastern Europe, the Caucasus and Central Asia.
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the developing world (except China), two regions account for the largest portion of increased CO2 emissions from 2004 to 2030: North America and Developing Asia. In Scenario A1B (which shows rapid economic growth, especially in developing nations), all of the increase in CO2 emissions occurs in the developing world: Developing Asia, Middle East/North Africa, Latin America and sub-Saharan Africa, in that order. Overall, average annual CO2 emissions growth is 1.5% in Scenario B2 and 2.4% in Scenario A1B over the 26-year period. For the purpose of estimating the CO2 mitigation potential in buildings, a baseline was derived based on the review of several studies. This baseline represents an aggregation of national and regional baselines reported in the studies (see Box 6.1). The building sector baseline derived and used in this chapter shows emissions between the B2 and A1B (SRES) scenarios, with 11.1 Gt of CO2-eq emissions in 2020 and 14.3 Gt in 2030 (including electricity emissions).
6.4 GHG mitigation options in buildings and equipment There is an extensive array of technologies that can be used to abate GHG emissions in new and existing residential and
U.S. commercial building energy use 2005 12% space heating 10% space cooling
commercial buildings. Prior to discussing options for reducing specific end-uses of energy in buildings it is useful to present an overview of energy end-uses in the residential and commercial sectors, where such information is available and to review some principles of energy-efficient design and operation that are broadly applicable. Figure 6.3 presents a breakdown of energy end-use in the residential and commercial sector for the United States and China. The single largest user of energy in residential buildings in both regions is space heating, followed by water heating (China) and other uses – primarily electric appliances (USA). The order of the next largest uses are reversed in China and the United States, suggesting that electric appliances will increase in use over time in China. The end-uses in commercial buildings are much less similar between China and the United States. For China, heating is by far the largest end-use. For the United States, the largest end-use is other (plug loads involving office equipment and small appliances). Water heating is the second end-use in China; it is not significant in commercial buildings in the United States. Lighting and cooling are similarly important as the third and fourth largest user in both countries. The single largest use of energy in residential buildings in both regions is for space heating, followed by water heating. Space heating is also the single largest use of energy in commercial
China commercial building energy use 2000 19% lighting and other 45% space heating
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Figure 6.3: Breakdown of residential and commercial sector energy use in United States (2005) and China (2000). Sources: EIA, 2006 and Zhou, 2007.
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buildings in the EU, accounting for up to 2/3 of total energy use and is undoubtedly dominant in the cold regions of China and in the Former Soviet Union. Lighting is sometimes the largest single use of electricity in commercial buildings, although in hot climates, air conditioning tends to be the single largest use of electricity. 6.4.1
Overview of energy efficiency principles
Design strategies for energy-efficient buildings include reducing loads, selecting systems that make the most effective use of ambient energy sources and heat sinks and using efficient equipment and effective control strategies. An integrated design approach is required to ensure that the architectural elements and the engineering systems work effectively together.
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6.4.1.4
The actual performance of a building depends as much on the quality of construction as on the quality of the design itself. Building commissioning is a quality control process that includes design review, functional testing of energy-consuming systems and components, and clear documentation for the owner and operators. Actual building energy performance also depends critically on how well the building is operated and maintained. Continuous performance monitoring, automated diagnostics and improved operator training are complementary approaches to improving the operation of commercial buildings in particular. 6.4.1.5
6.4.1.1
Utilize active solar energy and other environmental heat sources and sinks
The energy use of a building also depends on the behaviour and decisions of occupants and owners. Classic studies at Princeton University showed energy use variations of more than a factor of two between houses that were identical but had different occupants (Socolow, 1978). Levermore (1985) found a variation of 40% gas consumption and 54% electricity consumption in nine identical children’s homes in a small area of London. When those in charge of the homes knew that their consumption was being monitored, the electricity consumption fell. Behaviour of the occupants of non-residential buildings also has a substantial impact on energy use, especially when the lighting, heating and ventilation are controlled manually (Ueno et al., 2006). 6.4.1.6
Active solar energy systems can provide electricity generation, hot water and space conditioning. The ground, ground water, aquifers and open bodies of water, and less so air, can be used selectively as heat sources or sinks, either directly or by using heat pumps. Space cooling methods that dissipate heat directly to natural heat sinks without the use of refrigeration cycles (evaporative cooling, radiative cooling to the night sky, earth-pipe cooling) can be used. 6.4.1.3
Increase efficiency of appliances, heating and cooling equipment and ventilation
The efficiency of equipment in buildings continues to increase in most industrialized and many developing countries, as it has over the past quarter-century. Increasing the efficiency – and where possible reducing the number and size – of appliances, lighting and other equipment within conditioned spaces reduces energy consumption directly and also reduces cooling loads but increases heating loads, although usually by lesser amounts and possibly for different fuel types.
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Reduce heating, cooling and lighting loads
A simple strategy for reducing heating and cooling loads is to isolate the building from the environment by using high levels of insulation, optimizing the glazing area and minimizing the infiltration of outside air. This approach is most appropriate for cold, overcast climates. A more effective strategy in most other climates is to use the building envelope as a filter, selectively accepting or rejecting solar radiation and outside air, depending on the need for heating, cooling, ventilation and lighting at that time and using the heat capacity of the building structure to shift thermal loads on a time scale of hours to days. 6.4.1.2
Implement commissioning and improve operations and maintenance
Utilize system approaches to building design
Evaluation of the opportunities to reduce energy use in buildings can be done at the level of individual energy-using devices or at the level of building ‘systems’ (including building energy management systems and human behaviour). Energy efficiency strategies focused on individual energy-using devices or design features are often limited to incremental improvements. Examining the building as an entire system can lead to entirely different design solutions. This can result in new buildings that use much less energy but are no more expensive than conventional buildings. The systems approach in turn requires an integrated design process (IDP), in which the building performance is optimized through an iterative process that involves all members of the design team from the beginning. The steps in the most basic IDP for a commercial building include (i) selecting a highperformance envelope and highly efficient equipment, properly sized; (ii) incorporating a building energy management system that optimises the equipment operation and human behaviour, and (iii) fully commissioning and maintaining the equipment (Todesco, 2004). These steps alone can usually achieve energy savings in the order of 35–50% for a new commercial building, compared to standard practice, while utilization of more
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advanced or less conventional approaches has often achieved savings in the order of 50–80% (Harvey, 2006). 6.4.1.7
Consider building form, orientation and related attributes
portions of the remaining fluorocarbon content may be released, particularly if no specific measures are adopted to prevent such release. This raises the need to ensure that proper end-of-life management protocols are followed to avoid these unnecessary emissions.
At the early design stages, key decisions – usually made by the architect – can greatly influence the subsequent opportunities to reduce building energy use. These include building form, orientation, self-shading, height-to-floor-area ratio and decisions affecting the opportunities for and effectiveness of passive ventilation and cooling. Many elements of traditional building designs in both developed and developing countries have been effective in reducing heating and cooling loads. Urban design, including the clustering of buildings and mixing of different building types within a given area greatly affect the opportunities for and cost of district heating and cooling systems (Section 6.4.7) as well as transport energy demand and the shares of different transport modes (Chapter 5, Section 5.5.1).
6.4.2
6.4.1.8
Improvements in the thermal envelope can reduce heating requirements by a factor of two to four compared to standard practice, at a few percent of the total cost of residential buildings, and at little to no net incremental cost in commercial buildings when downsizing of heating and cooling systems is accounted for (Demirbilek et al., 2000; Hamada et al., 2003; Hastings, 2004). A number of advanced houses have been built in various cold-climate countries around the world that use as little as 10% of the heating energy of houses built according to the local national building code (Badescu and Sicre, 2003; Hamada et al., 2003; Hastings, 2004). Reducing the envelope and air exchange heat loss by a factor of two reduces the heating requirement by more than a factor of two because of solar gains and internal heat gains from equipment, occupants and lighting. In countries with mild winters but still requiring heating (including many developing countries), modest (and therefore less costly) amounts of insulation can readily reduce heating requirements by a factor of two or more, as well as substantially reducing indoor summer temperatures, thereby improving comfort (in the absence of air conditioning) or reducing summer cooling energy use (Taylor et al., 2000; Florides et al., 2002; Safarzadeh and Bahadori, 2005).
Minimize halocarbon emissions
Many building components – notably air conditioning and refrigeration systems, foam products used for insulation and other purposes and fire protection systems – may emit greenhouse gases with relatively high global-warming potentials. These chemicals include chlorofluorocarbons, hydrochlorofluorocarbons, halons (bromine-containing fluorocarbons) and hydrofluorocarbons (HFCs). While the consumption of the first three is being eliminated through the Montreal Protocol and various national and regional regulations, their on-going emission is still the subject of strategies discussed in the IPCC special report (IPCC/TEAP, 2005). Meanwhile, the use and emissions of HFCs, mostly as replacements for the three ozone-depleting substances, are increasing worldwide. For many air conditioning and refrigeration applications, the CO2 emitted during the generation of electricity to power the equipment will typically vastly outweigh the equivalent emissions of the HFC refrigerant. Some exceptions to this general rule exist and two building-related emission sources – CFC chillers and HFC supermarket refrigeration systems – are discussed further. In addition to these applications, some emission mitigation from air conditioning and refrigeration systems is achievable through easy, low-cost options including education and training, proper design and installation, refrigerant leakage monitoring and responsible use and handling of refrigerants throughout the equipment lifecycle. Like air conditioning and refrigeration systems, most foams and fire protection systems are designed to exhibit low leak rates, and therefore often only emit small portions of the total fluorocarbon under normal use conditions. Upon decommissioning of the building and removal and/or destruction of foam products and fire protection systems, however, large
Thermal envelope
The term ‘thermal envelope’ refers to the shell of the building as a barrier to unwanted heat or mass transfer between the interior of the building and the outside conditions. The effectiveness of the thermal envelope depends on (i) the insulation levels in the walls, ceiling and ground or basement floor, including factors such as moisture condensation and thermal bridges that affect insulation performance; (ii) the thermal properties of windows and doors; and (iii) the rate of exchange of inside and outside air, which in turn depends on the air-tightness of the envelope and driving forces such as wind, inside-outside temperature differences and air pressure differences due to mechanical ventilation systems or warm/cool air distribution.
6.4.2.1
Insulation
The choice of insulation material needs to maximize longterm thermal performance of the building element overall. As mentioned previously, this involves consideration of remaining thermal bridges and any water ingress, or other factor, which could result in deterioration of performance over time. For existing buildings, space may be at a premium and the most efficient insulation materials may be needed to minimize thicknesses required. Where upgrading of existing elements is essentially voluntary, minimization of cost and disturbance is equally important and a range of post-applied technologies can 395
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be considered, including cavity wall insulation, spray foams and rolled loft insulation. Only a few specific applications with effective control of end-of life emissions have been identified in which foams containing high GWP blowing agents will lead to lower overall climate impacts than hydrocarbon or CO2 solutions. However, where this is the case, care should still be taken to optimize life-cycle management techniques in order to minimize blowing agent emissions (see 6.4.15). 6.4.2.2
Windows
The thermal performance of windows has improved greatly through the use of multiple glazing layers, low-conductivity gases (argon in particular) between glazing layers, lowemissivity coatings on one or more glazing surfaces and use of framing materials (such as extruded fibreglass) with very low conductivity. Operable (openable) windows are available with heat flows that have only 25–35% of the heat loss of standard non-coated double-glazed (15 to 20% of singleglazed) windows. Glazing that reflects or absorbs a large fraction of the incident solar radiation reduces solar heat gain by up to 75%, thus reducing cooling loads. In spite of these technical improvements, the costs of glazing and windows has remained constant or even dropped in real terms (Jakob and Madlener, 2004). A major U.S. Department of Energy program is developing electrochromic and gasochromic windows which can dynamically respond to heating and cooling in different seasons. 6.4.2.3
Air leakage
In cold climates, uncontrolled exchange of air between the inside and outside of a building can be responsible for up to half of the total heat loss. In hot-humid climates, air leakage can be a significant source of indoor humidity. In residential construction, installation in walls of a continuous impermeable barrier, combined with other measures such as weatherstripping, can reduce rates of air leakage by a factor of five to ten compared to standard practice in most jurisdictions in North America, Europe and the cold-climate regions of Asia (Harvey, 2006). In addition to leakage through the building envelope, recent research in the United States has demonstrated that leaks in ducts for distributing air for heating and cooling can increase heating and cooling energy requirements by 20–40% (Sherman and Jump, 1997; O’Neal et al., 2002; Francisco et al., 2004). A technology in early commercial use in the United States seals leaks by spraying fine particles into ducts. The sticky particles collect at leakage sites and seal them permanently. This technology is cost-effective for many residential and commercial buildings; it achieves lower costs by avoiding the labour needed to replace or manually repair leaky ducts.
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6.4.3 6.4.3.1
Heating systems Passive solar heating
Passive solar heating can involve extensive sun-facing glazing, various wall- or roof-mounted solar air collectors, double-façade wall construction, airflow windows, thermally massive walls behind glazing and preheating or pre-cooling of ventilation air through buried pipes. Technical details concerning conventional and more advanced passive solar heating techniques, real-world examples and data on energy savings are provided in books by Hastings (1994), Hestnes et al. (2003) and Hastings (2004). Aggressive envelope measures combined with optimisation of passive solar heating opportunities, as exemplified by the European Passive House Standard, have achieved reductions in purchased heating energy by factors of five to thirty (i.e., achieving heating levels less than 15 kWh/ m2/yr even in moderately cold climates, compared to 220 and 250–400 kWh/m2/yr for the average of existing buildings in Germany and Central/Eastern Europe, respectively (Krapmeier and Drössler, 2001; Gauzin-Müller, 2002; Kostengünstige Passivhäuser als europäische Standards, 2005). 6.4.3.2
Space heating systems
In the industrialized nations and in urban areas in developing countries (in cold winter climates), heating is generally provided by a district heating system or by an onsite furnace or boiler. In rural areas of developing countries, heating (when provided at all) is generally from direct burning of biomass. The following sections discuss opportunities to increase energy efficiency in these systems. Heating systems used primarily in industrialized countries Multi-unit residences and many single-family residences (especially in Europe) use boilers, which produce steam or hot water that is circulated, generally through radiators. Annual Fuel Utilization Efficiencies (AFUE) values range from 80% to 99% for the boiler, not including distribution losses. Modern residential forced-air furnaces, which are used primarily in North America, have AFUE values ranging from 78% to 97% (again, not including distribution system losses). Old equipment tends to have an efficiency in the range of 60–70%, so new equipment can provide substantial savings (GAMA (Gas Appliance Manufacturers Association), 2005). In both boilers and furnaces, efficiencies greater than about 88% require condensing operation, in which some of the water vapour in the exhaust is condensed in a separate heat exchanger. Condensing boilers are increasingly used in Western Europe due to regulation of new buildings, which require higher-efficiency systems. Hydronic systems (in which water rather than air is circulated), especially floor radiant heating systems, are capable of greater energy efficiency than forced air systems because of the low energy required to distribute a given amount of heat, low distribution heat losses and absence of induced infiltration of
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outside air into the house due to poorly balanced air distribution systems (low-temperature systems also make it possible to use low-grade solar thermal energy). Heat pumps use an energy input (almost always electricity) to transfer heat from a cold medium (the outside air or ground in the winter) to a warmer medium (the warm air or hot water used to distribute heat in a building). During hot weather, the heat pump can operate in reverse, thereby cooling the indoor space. In winter, drawing heat from a relatively warm source (such as the ground rather than the outside air) and distributing the heat at the lowest possible temperature can dramatically improve the heat pump efficiency. Use of the ground rather than the outside air as a heat source reduced measured energy use for heating by 50 to 60% in two US studies (Shonder et al., 2000; Johnson, 2002). Due to the large energy losses (typically 60–65%) in generating electricity from fossil fuels, heat pumps are particularly advantageous for heating when they replace electric-resistance heating, but may not be preferable to direct use of fuels for heating. The ground can also serve as a lowtemperature heat sink in summer, increasing the efficiency of air conditioning. Coal and biomass burning stoves in rural areas of developing countries Worldwide, about three billion people use solid fuels – biomass and, mainly in China, coal – in household stoves to meet their cooking, water heating and space heating needs. Most of these people live in rural areas with little or no access to commercial sources of fuel or electricity (WEC (World Energy Council and Food and Agriculture Organization), 1999). Statistical information on fuel use in cooking stoves is sketchy, so any estimates of energy use and associated GHG emissions are uncertain.5 The global total for traditional biofuel use – a good proxy for energy use in household stoves – was about 32 EJ in 2002, compared to commercial energy use worldwide of 401 EJ (IEA, 2004c). Worldwide, most household stoves use simple designs and local materials that are inefficient, highly polluting and contribute to the overuse of local resources. Studies of China and India have found that if only the Kyoto Protocol basket of GHGs is considered, biomass stoves appear to have lower emission factors than fossil-fuel alternatives (Smith et al., 2000; Edwards et al., 2004). If products of incomplete combustion (PICs) other than methane and N2O are considered, however, then biomass stove-fuel combinations exhibit GHG emissions three to ten times higher than fossil-fuel alternatives, and in many cases even higher emissions than from stoves burning coal briquettes (Goldemberg et al., 2000). Additional heating effects arise from black carbon emissions associated with woodburning stoves. Programmes to develop and disseminate moreefficient biomass stoves have been very effective in China, less
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so in India and other countries (Barnes et al., 1994; Goldemberg et al., 2000; Sinton et al., 2004). In the long term, stoves that use biogas or biomass-derived liquid fuels offer the greatest potential for significantly reducing the GHG (and black carbon) emissions associated with household use of biomass fuels. 6.4.4
Cooling and cooling loads
Cooling energy can be reduced by: 1) reducing the cooling load on a building, 2) using passive techniques to meet some or all of the load, and 3) improving the efficiency of cooling equipment and thermal distribution systems. 6.4.4.1
Reducing the cooling load
Reducing the cooling load depends on the building shape and orientation, the choice of building materials and a whole host of other decisions that are made in the early design stage by the architect and are highly sensitive to climate. In general, recently constructed buildings are no longer adapted to prevailing climate; the same building forms and designs are now seen in Stockholm, New York, Houston, Hong Kong, Singapore and Kuwait. However, the principles of design to reduce cooling load for any climate are well known. In most climates, they include: (i) orienting a building to minimize the wall area facing east or west; (ii) clustering buildings to provide some degree of self shading (as in many traditional communities in hot climates); (iii) using high-reflectivity building materials; (iv) increasing insulation; (v) providing fixed or adjustable shading; (vi) using selective glazing on windows with a low solar heat gain and a high daylight transmission factor and avoiding excessive window area (particularly on east- and west-facing walls); and (vii) utilizing thermal mass to minimize daytime interior temperature peaks. As well, internal heat loads from appliances and lighting can be reduced through the use of efficient equipment and controls. Increasing the solar reflectivity of roofs and horizontal or near-horizontal surfaces around buildings and planting shade trees can yield dramatic energy savings. The benefits of trees arise both from direct shading and from cooling the ambient air. Rosenfeld et al. (1998) computed that a very large-scale, citywide program of increasing roof and road albedo and planting trees in Los Angeles could yield a total savings in residential cooling energy of 50–60%, with a 24–33% reduction in peak air conditioning loads. 6.4.4.2
Passive and low-energy cooling techniques
Purely passive cooling techniques require no mechanical energy input, but can often be greatly enhanced through small amounts of energy to power fans or pumps. A detailed discussion of passive and low-energy cooling techniques can be found in
Estimates are available for China and India, collectively home to about one third of the world’s population. Residential use of solid fuels in China, nearly all used in stoves, was about 9 EJ in 2002, or 18% of all energy use in the country (National Bureau of Statistics, 2004). The corresponding figures for India were 8 EJ and 36% (IEA, 2004c). In both cases, nearly all of this energy is in the form of biomass.
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Harvey (2006) and Levermore (2000). Highlights are presented below: Natural and night-time ventilation Natural ventilation reduces the need for mechanical cooling by: directly removing warm air when the incoming air is cooler than the outgoing air, reducing the perceived temperature due to the cooling effect of air motion, providing night-time cooling of exposed thermal mass and increasing the acceptable temperature through psychological adaptation when the occupants have control of operable windows. When the outdoor temperature is 30°C, the average preferred temperature in naturally ventilated buildings is 27°C, compared to 25°C in mechanically ventilated buildings (de Dear and Brager, 2002). Natural ventilation requires a driving force and an adequate number of openings, to produce airflow. Natural ventilation can be induced through pressure differences arising from insideoutside temperature differences or from wind. Design features, both traditional and modern, that create thermal driving forces and/or utilize wind effects include courtyards, atria, wind towers, solar chimneys and operable windows (Holford and Hunt, 2003). In addition to being increasingly employed in commercial buildings in Europe, natural ventilation is starting to be used in multi-story commercial buildings in more temperate climates in North America (McConahey et al., 2002). Natural ventilation can be supplemented with mechanical ventilation as needed. In climates with a minimum diurnal temperature variation of 5°C to 7°C, natural or mechanically assisted night-time ventilation, in combination with exposed thermal mass, can be very effective in reducing daily temperature peaks and, in some cases, eliminating the need for cooling altogether. Simulations carried out in California indicate that night-time ventilation is sufficient to prevent peak indoor temperatures from exceeding 26°C over 43% of California in houses with an improved envelope and modestly greater thermal mass compared to standard practice (Springer et al., 2000). For Beijing, da Graça et al. (2002) found that thermally and wind-driven night-time ventilation could eliminate the need for air conditioning of a six-unit apartment building during most of the summer if the high risk of condensation during the day due to moist outdoor air coming into contact with the night-cooled indoor surfaces could be reduced. Evaporative cooling There are two methods of evaporatively cooling the air supplied to buildings. In a ‘direct’ evaporative cooler, water evaporates directly into the air stream to be cooled. In an ‘indirect’ evaporative cooler, water evaporates into and cools a secondary air stream, which cools the supply air through a heat exchanger without adding moisture. By appropriately combining direct and indirect systems, evaporative cooling can provide comfortable conditions most of the time in most parts of the world. 398
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Subject to availability of water, direct evaporative cooling can be used in arid areas; indirect evaporative cooling extends the region of applicability to somewhat more humid climates. A new indirect-direct evaporative cooler in the development phase indicated savings in annual cooling energy use of 92 to 95% for residences and 89 to 91% for a modular school classroom in simulations for a variety of California climate zones (DEG, 2004). Other passive cooling techniques Underground earth-pipe cooling consists of cooling ventilation air by drawing outside air through a buried air duct. Good performance depends on the climate having a substantial annual temperature range. Desiccant dehumidification and cooling involves using a material (desiccant) that removes moisture from air and is regenerated using heat. Solid desiccants are a commercially available technology. The energy used for dehumidification can be reduced by 30 to 50% compared to a conventional overcooling/reheat scheme (50 to 75% savings of conventional sources if solar energy is used to regenerate the desiccant) (Fischer et al., 2002; Niu et al., 2002). In hot-humid climates, desiccant systems can be combined with indirect evaporative cooling, providing an alternative to refrigerationbased air conditioning systems (Belding and Delmas, 1997). 6.4.4.3
Air conditioners and vapour-compression chillers
Air conditioners used for houses, apartments and small commercial buildings have a nominal COP (cooling power divided by fan and compressor power, a direct measure of efficiency) ranging from 2.2 to 3.8 in North America and Europe, depending on operating conditions. More efficient mini-split systems are available in Japan, ranging from 4.5 to 6.2 COP for a 2.8 kW cooling capacity unit. Chillers are larger cooling devices that produce chilled water (rather than cooled air) for use in larger commercial buildings. COP generally increases with size, with the largest and most efficient centrifugal chillers having a COP of up to 7.9 under full-load operation and even higher under part-load operation. Although additional energy is used in chiller-based systems for ventilation, circulating chilled water and operating a cooling tower, significant energy savings are possible through the choice of the most efficient cooling equipment in combination with efficient auxiliary systems (see Section 6.4.5.1 for principles). Air conditioners – from small room-sized units to large building chillers – generally employ a halocarbon refrigerant in a vapour-compression cycle. Although the units are designed to exhibit low refrigerant emission rates, leaks do occur and additional emissions associated with the installation, service and disposal of this equipment can be significant. The emissions will vary widely from one installation to the next and depend greatly on the practices employed at the site. In some cases, the GWPweighted lifetime emissions of the refrigerant will outweigh the CO2 emissions associated with the electricity, highlighting the need to consider refrigerant type and handling as well as energy
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efficiency when making decisions on the purchase, operation, maintenance and replacement of these systems. Until recently, the penetration of air conditioning in developing countries has been relatively low, typically only used in large office buildings, hotels and high-income homes. That is quickly changing however, with individual apartment and home air conditioning becoming more common in developing countries, reaching even greater levels in developed countries. This is evident in the production trends of typical room-tohouse sized units, which increased 26% (35.8 to 45.4 million units) from 1998 to 2001 (IPCC/TEAP, 2005). 6.4.5
Heating, ventilation and air conditioning (HVAC) systems
while computer simulations by Jaboyedoff et al. (2004) and by Jakob et al. (2006) indicate that increasing the thermostat by 2°C to 4°C will reduce annual cooling energy use by more than a factor of three for a typical office building in Zurich, and by a factor of two to three if the thermostat setting is increased from 23°C to 27°C for night-time air conditioning of bedrooms in apartments in Hong Kong (Lin and Deng, 2004). Additional savings can be obtained in ‘mixed-mode’ buildings, in which natural ventilation is used whenever possible, making use of the extended comfort range associated with operable windows, and mechanical cooling is used only when necessary during periods of very warm weather or high building occupancy. 6.4.5.2
The term HVAC is generally used in reference to commercial buildings. HVAC systems include filtration and, where required by the climate, humidification and dehumidification as well as heating and cooling. However, energy-efficient houses in climates with seasonal heating are almost airtight, so mechanical ventilation has to be provided (during seasons when windows will be closed), often in combination with the heating and/or cooling system, as in commercial buildings. 6.4.5.1
Principles of energy-efficient HVAC design
In the simplest HVAC systems, heating or cooling is provided by circulating a fixed amount of air at a sufficiently warm or cold temperature to maintain the desired room temperature. The rate at which air is circulated in this case is normally much greater than that needed for ventilation to remove contaminants. During the cooling season, the air is supplied at the coldest temperature needed in any zone and reheated as necessary just before entering other zones. There are a number of changes in the design of HVAC systems that can achieve dramatic savings in the energy use for heating, cooling and ventilation. These include (i) using variable-air volume systems so as to minimize simultaneous heating and cooling of air; (ii) using heat exchangers to recover heat or coldness from ventilation exhaust air; (iii) minimizing fan and pump energy consumption by controlling rotation speed; (iv) separating the ventilation from the heating and cooling functions by using chilled or hot water for temperature control and circulating only the volume of air needed for ventilation; (v) separating cooling from dehumidification functions through the use of desiccant dehumidification; (vi) implementing a demand-controlled ventilation system in which ventilation airflow changes with changing building occupancy which alone can save 20 to 30% of total HVAC energy use (Brandemuehl and Braun, 1999); (vii) correctly sizing all components; and (viii) allowing the temperature maintained by the HVAC system to vary seasonally with outdoor conditions (a large body of evidence indicates that the temperature and humidity set-points commonly encountered in air-conditioned buildings are significantly lower than necessary (de Dear and Brager, 1998; Fountain et al., 1999),
Alternative HVAC systems in commercial buildings
The following paragraphs describe two alternatives to conventional HVAC systems in commercial buildings that together can reduce the HVAC system energy use by 30 to 75%. These savings are in addition to the savings arising from reducing heating and cooling loads. Radiant chilled-ceiling cooling A room may be cooled by chilling a large fraction of the ceiling by circulating water through pipes or lightweight panels. Chilled ceiling (CC) cooling has been used in Europe since at least the mid-1970s. In Germany during the 1990s, 10% of retrofitted buildings used CC cooling (Behne, 1999). Significant energy savings arise because of the greater effectiveness of water than air in transporting heat and because the chilled water is supplied at 16°C to 20°C rather than at 5°C to 7°C. This allows a higher chiller COP when the chiller operates, but also allows more frequent use of ‘water-side free cooling,’ in which the chiller is bypassed altogether and water from the cooling tower is used directly for space cooling. For example, a cooling tower alone could directly meet the cooling requirements 97% of the time in Dublin, Ireland and 67% of the time in Milan, Italy if the chilled water is supplied at 18°C (Costelloe and Finn, 2003). Displacement ventilation Conventional ventilation relies on turbulent mixing to dilute room air with ventilation air. A superior system is ‘displacement ventilation’ (DV) in which air is introduced at low speed through many diffusers in the floor or along the sides of a room and is warmed by internal heat sources (occupants, lights, plug-in equipment) as it rises to the top of the room, displacing the air already present. The thermodynamic advantage of displacement ventilation is that the supply air temperature is significantly higher for the same comfort conditions (about 18oC compared with about 13oC in a conventional mixing ventilation system). It also permits significantly smaller airflow. DV was first applied in northern Europe; by 1989 it had captured 50% of the Scandinavian market for new industrial buildings and 25% for new office buildings (Zhivov and 399
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Rymkevich, 1998). The building industry in North America has been much slower to adopt DV; by the end of the 1990s fewer than 5% of new buildings used under-floor air distribution systems (Lehrer and Bauman, 2003). Overall, DV can reduce energy use for cooling and ventilation by 30 to 60%, depending on the climate (Bourassa et al., 2002; Howe et al., 2003). 6.4.6
Building energy management systems (BEMS)
BEMSs are control systems for individual buildings or groups of buildings that use computers and distributed microprocessors for monitoring, data storage and communication (Levermore, 2000). The BEMS can be centrally located and communicate over telephone or Internet links with remote buildings having ‘outstations’ so that one energy manager can manage many buildings remotely. With energy meters and temperature, occupancy and lighting sensors connected to a BEMS, faults can be detected manually or using automated fault detection software (Katipamula et al., 1999), which helps avoid energy waste (Burch et al., 1990). With the advent of inexpensive, wireless sensors and advances in information technology, extensive monitoring via the Internet is possible. Estimates of BEMS energy savings vary considerably: up to 27% (Birtles and John, 1984); between 5% and 40% (Hyvarinen, 1991; Brandemuehl and Bradford, 1999; Brandemuehl and Braun, 1999; Levermore, 2000); up to 20% in space heating energy consumption and 10% for lighting and ventilation; and 5% to 20% overall (Roth et al., 2005). 6.4.6.1
Commissioning
Proper commissioning of the energy systems in a commercial building is a key to efficient operation (Koran, 1994; Kjellman et al., 1996; IEA, 2005; Roth et al., 2005). Building commissioning is a quality control process that begins with the early stages of design. Commissioning helps ensure that the design intent is clear and readily tested, that installation is subjected to onsite inspection and that all systems are tested and functioning properly before the building is accepted. A systems manual is prepared to document the owner’s requirements, the design intent (including as-built drawings), equipment performance specifications and control sequences. Recent results of building commissioning in the USA showed energy savings of up to 38% in cooling and/or 62% in heating and an average higher than 30% (Claridge et al., 2003). A study by Mills et al. (2005) reviewed data from 224 US buildings that had been commissioned or retro-commissioned. The study found that the costs of commissioning new buildings were typically outweighed by construction cost savings due to fewer change orders and that retro-commissioning produced median energy savings of 15% with a median payback period of 8.5 months. It is very difficult to assess the energy benefits of commissioning new buildings due to the lack of a baseline. 400
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6.4.6.2
Operation, maintenance and performance benchmarking
Once a building has been commissioned, there is a need to maintain its operating efficiency. A variety of methods to monitor and evaluate performance and diagnose problems are currently under development (Brambley et al., 2005). Postoccupancy evaluation (POE) is a useful complement to ongoing monitoring of equipment and is also useful for ensuring that the building operates efficiently. A UK study of recently constructed buildings found that the use of POE identified widespread energy wastage (Bordass et al., 2001a; Bordass et al., 2001b). Cogeneration and District Heating/Cooling Buildings are usually part of a larger community. If the heating, cooling and electricity needs of a larger collection of buildings can be linked together in an integrated system without major distribution losses, then significant savings in primary energy use are possible – beyond what can be achieved by optimising the design of a single building. Community-scale energy systems also offer significant new opportunities for the use of renewable energy. Key elements of an integrated system can include: 1) district heating networks for the collection of waste or surplus heat and solar thermal energy from dispersed sources and its delivery to where it is needed; 2) district cooling networks for the delivery of chilled water for cooling individual buildings; 3) central production of steam and/or hot water in combination with the generation of electricity (cogeneration) and central production of cold water; 4) production of electricity through photovoltaic panels mounted on or integrated into the building fabric; 5) diurnal storage of heat and coldness produced during off-peak hours or using excess wind-generated electricity; and 6) seasonal underground storage of summer heat and winter coldness. District heating (DH) is widely used in regions with large fractions of multi-family buildings, providing as much as 60% of heating and hot water energy needs for 70% of the families in Eastern European countries and Russia (OECD/IEA, 2004). While district heating can have major environmental benefits over other sources of heat, including lower specific GHG emissions, systems in these countries suffer from the legacies of past mismanagement and are often obsolete, inefficient and expensive to operate (Lampietti and Meyer, 2003, ÜrgeVorsatz et al., 2006). Making DH more efficient could save 350 million tonnes of CO2 emissions in these countries annually, accompanied by significant social, economic and political benefits (OECD/IEA, 2004). The greatest potential improvement in the efficiency of district heating systems is to convert them to cogeneration systems that involve the simultaneous production of electricity and useful heat. For cogeneration to provide an improvement in efficiency, a use has to be found for the waste heat. Centralized production of heat in a district heat system can be more efficient than onsite boilers or furnaces even in the absence of cogeneration
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and in spite of distribution losses, if a district-heating network is used with heat pumps to upgrade and distribute heat from scattered sources. Examples include waste heat from sewage in Tokyo (Yoshikawa, 1997) and Gothenberg, Sweden (Balmér, 1997) and low-grade geothermal heat in Tianjin, China, that is left over after higher-temperature heat has been used for heating and hot water purposes (Zhao et al., 2003). Waste heat from incineration has been used, particularly in northern Europe. Chilled water supplied to a district-cooling network can be produced through trigeneration (the simultaneous production of electricity, heat and chilled water), or it can be produced through a centralized chilling plant independent of power generation. District cooling provides an alternative to separate chillers and cooling towers in multi-unit residential buildings that would otherwise use inefficient small air conditioners. In spite of the added costs of pipes and heat exchangers in district heating and cooling networks, the total capital cost can be less than the total cost of heating and cooling units in individual buildings, (Harvey, 2006, Chapter 15). Adequate control systems are critical to the energy-efficient operation of both district cooling and central (building-level) cooling systems. District heating and cooling systems, especially when combined with some form of thermal energy storage, make it more economically and technically feasible to use renewable sources of energy for heating and cooling. Solar-assisted district heating systems with storage can be designed such that solar energy provides 30 to 95% of total annual heating and hot water requirements under German conditions (Lindenberger et al., 2000). Sweden has been able to switch a large fraction of its building heating energy requirements to biomass energy (plantation forestry) for its district heating systems (Swedish Energy Agency, 2004). 6.4.7
Active collection and transformation of solar energy
Buildings can serve as collectors and transformers of solar energy, meeting a large fraction of their energy needs on a sustainable basis with minimal reliance on connection to energy grids, although for some climates this may only apply during the summer. As previously discussed, solar energy can be used for daylighting, for passive heating and as one of the driving forces for natural ventilation, which can often provide much or all of the required cooling. By combining a high-performance thermal envelope with efficient systems and devices, 50–75% of the heating and cooling energy needs of buildings as constructed under normal practice can either be eliminated or satisfied through passive solar design. Electricity loads, especially in commercial buildings, can be drastically reduced to a level that allows building-integrated photovoltaic panels (BiPV) to meet much of the remaining electrical demand
6
during daytime hours. Photovoltaic panels can be supplemented by other forms of active solar energy, such as solar thermal collectors for hot water, space heating, absorption space cooling and dehumidification. 6.4.7.1
Building-integrated PV (BiPV)
The principles governing photovoltaic (PV) power generation and the prospects for centralized PV production of electricity are discussed in Chapter 4, Section 4.3.3.6. Building-integrated PV (BiPV) consists of PV modules that function as part of the building envelope (curtain walls, roof panels or shingles, shading devices, skylights). BiPV systems are sometimes installed in new ‘showcase’ buildings even before the systems are generally cost-effective. These early applications will increase the rate at which the cost of BiPVs comes down and the technical performance improves. A recent report presents data on the cost of PV modules and the installed-cost of PV systems in IEA countries (IEA, 2003b). Electricity costs from BiPV at present are in the range of 0.30–0.40 US$/kWh in good locations, but can drop considerably with mass production of PV modules (Payne et al., 2001). Gutschner et al. (2001) have estimated the potential for power production from BiPV in IEA member countries. Estimates of the percentage of present total national electricity demand that could be provided by BiPV range from about 15% (Japan) to almost 60% (USA). 6.4.7.2
Solar thermal energy for heating and hot water
Most solar thermal collectors used in buildings are either flat-plate or evacuated-tube collectors.6 Integrated PV/thermal collectors (in which the PV panel serves as the outer part of a thermal solar collector) are also commercially available (Bazilian et al., 2001; IEA, 2002). ‘Combisystems’ are solar systems that provide both space and water heating. Depending on the size of panels and storage tanks, and the building thermal envelope performance, 10 to 60% of the combined hot water and heating demand can be met by solar thermal systems at central and northern European locations. Costs of solar heat have been 0.09–0.13 €/kWh for large domestic hot water systems and 0.40–0.50 €/kWh for combisystems with diurnal storage (Peuser et al., 2002). Worldwide, over 132 million m2 of solar collector surface for space heating and hot water were in place by the end of 2003. China accounts for almost 40% of the total (51.4 million m2), followed by Japan (12.7 million m2) and Turkey (9.5 million m2) (Weiss et al., 2005).
See Peuser et al. (2002) and Andén (2003) for technical information.
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6.4.8
Domestic hot water
Options to reduce fossil or electrical energy used to produce hot water include (i) use of water saving fixtures, more waterefficient washing machines, cold-water washing and (if used at all) more water-efficient dishwashers (50% typical savings); (ii) use of more efficient and better insulated water heaters or integrated space and hot-water heaters (10–20% savings); (iii) use of tankless (condensing or non-condensing) water heaters, located close to the points of use, to eliminate standby and greatly reduce distribution heat losses (up to 30% savings, depending on the magnitude of standby and distribution losses with centralized tanks); (v) recovery of heat from warm waste water; (vi) use of air-source or exhaust-air heat pumps; and (vii) use of solar thermal water heaters (providing 50–90% of annual hot-water needs, depending on climate). The integrated effect of all of these measures can frequently reach a 90% savings. Heat pumps using CO2 as a working fluid are an attractive alternative to electric-resistance hot water heaters, with a COP of up to 4.2–4.9 (Saikawa et al., 2001; Yanagihara, 2006).
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referred to as ‘task/ambient lighting’ and is popular in Europe. Not only can this alone cut lighting energy use in half, but it provides a greater degree of individual control over personal lighting levels and can reduce uncomfortable levels of glare and high contrast. About one third of the world’s population depends on fuel-based lighting (such as kerosene, paraffin or diesel), contributing to the major health burden from indoor air pollution in developing countries. While these devices provide only 1% of global lighting, they are responsible for 20% of the lighting-related CO2 emissions and consume 3% of the world’s oil supply. A CFL or LED is about 1000 times more efficient than a kerosene lamp (Mills, 2005). Efforts are underway to promote replacement of kerosene lamps with LEDs in India. Recent advances in light-emitting diode (LED) technology have significantly improved the cost-effectiveness, longevity and overall viability of stand-alone PV-powered task lighting (IEA, 2006b). 6.4.10 Daylighting
6.4.9
Lighting systems
Lighting energy use can be reduced by 75 to 90% compared to conventional practice through (i) use of daylighting with occupancy and daylight sensors to dim and switch off electric lighting; (ii) use of the most efficient lighting devices available; and (iii) use of such measures as ambient/task lighting. 6.4.9.1
High efficiency electric lighting
Presently 1.9 GtCO2 are emitted by electric lighting worldwide, equivalent to 70% of the emissions from light passenger vehicles (IEA, 2006b). Continuous improvements in the efficacy7 of electric lighting devices have occurred during the past decades and can be expected to continue. Advances in lamps have been accompanied by improvements in occupancy sensors and reductions in cost (Garg and Bansal, 2000; McCowan et al., 2002). A reduction in residential lighting energy use of a factor of four to five can be achieved compared to incandescent/halogen lighting. For lighting systems providing ambient (general space) lighting in commercial buildings, the energy required can be reduced by 50% or more compared to old fluorescent systems through use of efficient lamps (ballasts and reflectors, occupancy sensors, individual or zone switches on lights and lighter colour finishes and furnishings. A further 40 to 80% of the remaining energy use can be saved in perimeter zones through daylighting (Rubinstein and Johnson, 1998; Bodart and Herde, 2002). A simple strategy to further reduce energy use is to provide a relatively low background lighting level, with local levels of greater illumination at individual workstations. This strategy is
7
This is the ratio of light output in lumens to input power in watts.
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Daylighting systems involve the use of natural lighting for the perimeter areas of a building. Such systems have light sensors and actuators to control artificial lighting. Opportunities for daylighting are strongly influenced by architectural decisions early in the design process, such as building form; the provision of inner atria, skylights and clerestories (glazed vertical steps in the roof); and the size, shape and position of windows. IEA (2000) provides a comprehensive sourcebook of conventional and less conventional techniques and technologies for daylighting. A number of recent studies indicate savings in lighting energy use of 40 to 80% in the daylighted perimeter zones of office buildings (Rubinstein and Johnson, 1998; Jennings et al., 2000; Bodart and Herde, 2002; Reinhart, 2002; Atif and Galasiu, 2003; Li and Lam, 2003). The management of solar heat gain along with daylighting to reduce electric lighting also leads to a reduction in cooling loads. Lee et al. (1998) measured savings for an automated Venetian blind system integrated with office lighting controls, finding that lighting energy savings averaged 35% in winter and ranged from 40 to 75% in summer. Monitored reductions in summer cooling loads were 5 to 25% for a southeast-facing office in Oakland, California building, with even larger reductions in peak cooling loads. Ullah and Lefebvre (2000) reported measured savings of 13 to 32% for cooling plus ventilation energy using automatic blinds in a building in Singapore. An impediment to more widespread use of daylighting is the linear, sequential nature of the design process. Based on a survey of 18 lighting professionals in the USA, Turnbull
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and Loisos (2000) found that, rather than involving lighting consultants from the very beginning, architects typically make a number of irreversible decisions at an early stage of the design that adversely impact daylighting, ‘then’ pass on their work to the lighting consultants and electrical engineers to do the lighting design. As a result, the lighting system becomes, de facto, strictly an electrical design. 6.4.11 Household appliances, consumer electronics and office equipment Energy use by household appliances, office equipment and consumer electronics, from now on referred to as ‘appliances’, is an important fraction of total electricity use in both households and workplaces (Kawamoto et al., 2001; Roth et al., 2002). This equipment is more than 40% of total residential primary energy demand in 11 large OECD nations8 (IEA, 2004f). The largest growth in electricity demand has been in miscellaneous equipment (home electronics, entertainment, communications, office equipment and small kitchen equipment), which has been evident in all industrialized countries since the early 1980s. Such miscellaneous equipment now accounts for 70% of all residential appliance electricity use in the 11 large OECD nations (IEA, 2004f). Appliances in some developing countries constitute a smaller fraction of residential energy demand. However, the rapid increase in their saturation in many dynamically developing countries such as China, especially in urban areas, demonstrates the expected rise in importance of appliances in the developing world as economies grow (Lawrence Berkeley National Laboratory, 2004). On a primary energy basis appliances undoubtedly represent a larger portion of total energy use for residential than for commercial buildings. In the United States, for example, they account for almost 55% of total energy consumption in commercial buildings. Miscellaneous equipment and lighting combined account for more than half of total energy consumption in commercial buildings in the United States and Japan (Koomey et al., 2001; Murakami et al., 2006). The most efficient appliances require a factor of two to five less energy than the least efficient appliances available today. For example, in the USA, the best horizontal-axis clotheswashing machines use less than half the energy of the best vertical-axis machines (FEMP, 2002), while refrigerator/freezer units meeting the current US standard (478 kWh/yr) require about 25% of the energy used by refrigerator/freezers sold in the USA in the late 1970s (about 1800 kWh/yr) and about 50% of energy used in the late 1980s. Available refrigerator/freezers of standard US size use less than 400 kWh/yr (Brown et al., 1998). However, this is still in excess of the average energy use by (generally smaller) refrigerators in Sweden, the Netherlands, Germany and Italy in the late 1990s (IEA, 2004f).
8
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Standby and low power mode use by consumer electronics (i.e., energy used when the machine is turned off) in a typical household in many countries often exceeds the energy used by a refrigerator/freezer unit that meets the latest US standards, that is often more than 500 kWh/yr, (Bertoldi et al., 2002). The growing proliferation of electronic equipment such as set-top boxes for televisions, a wide variety of office equipment (in homes as well as offices) and sundry portable devices with attendant battery chargers – combined with inefficient power supplies (Calwell and Reeder, 2002) and highly inefficient circuit designs that draw unnecessary power in the resting or standby modes – have caused this equipment to be responsible for a large fraction of the electricity demand growth in both residential and commercial buildings in many nations. Efforts are underway especially at the International Energy Agency and several countries (e.g., Korea, Australia, Japan and China) to reduce standby energy use by a factor of two to three (Ross and Meier, 2002; Fung et al., 2003). Electricity use by office equipment may not yet be large compared to electricity use by the HVAC system, but (as noted) it is growing rapidly and is already an important source of internal heat gain in offices and some other commercial buildings. The biggest savings opportunities are: 1) improved power supply efficiency in both active and low-power modes, 2) redesigned computer chips that reduce electricity use in low-power mode, and 3) repeated reminders to users to turn equipment off during non-working hours. The cooking stove, already referred to in Section 6.4.3.2 for heating, is a major energy-using appliance in developing countries. However, there is particular concern about emissions of products of incomplete combustion described in that section. Two-and-a-half billion people in developing countries depend on biomass, such as wood, dung, charcoal and agricultural residues, to meet their cooking energy needs (IEA, 2006e). Options available to reduce domestic cooking energy needs include: 1) improved efficiency of biomass stoves; 2) improved access to clean cooking fuels, both liquid and gaseous; 3) access to electricity and low-wattage and low-cost appliances for low income households; 4) non-electric options such as solar cookers; 5) efficient gas stoves; and 6) small electric cooking equipment such as microwaves, electric kettles or electric frying pans. Improved biomass stoves can save from 10 to 50% of biomass consumption for the same cooking service (REN21 (Renewable Energy Policy Network), 2005) at the same time reducing indoor air pollution by up to one-half. Although the overall impact on emissions from fuel switching can be either positive or negative, improved modern fuels and greater conversion efficiency would result in emission reductions from all fuels (IEA, 2006e).
Australia, Denmark, Finland, France, Germany, Italy, Japan, Norway, Sweden, the United Kingdom, and the United States.
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6.4.12 Supermarket refrigeration systems Mitigation options for food-sales and service buildings, especially supermarkets and hypermarkets extend beyond the energy savings mitigation options reviewed so far (e.g., high efficiency electric lighting, daylighting, etc.). Because these buildings often employ large quantities of HFC refrigerants in extensive and often leaky systems, a significant share of total GHG emissions are due to the release of the refrigerant. In all, emissions of the refrigerant can be greater than the emissions due to the system energy use (IPCC/TEAP, 2005). Two basic mitigation options are reviewed in IPCC/TEAP report: leak reduction and alternative system design. Refrigerant leakage rates are estimated to be around 30% of banked system charge. Leakage rates can be reduced by system design for tightness, maintenance procedures for early detection and repairs of leakage, personnel training, system leakage record keeping and end-of-life recovery of refrigerant. Alternative system design involves for example, applying direct systems using alternative refrigerants, better containment, distributed systems, indirect systems or cascade systems. It was found that up to 60% lower LCCP values can be obtained by alternative system design (IPCC/TEAP, 2005). 6.4.13 Energy savings through retrofits There is a large stock of existing and inefficient buildings, most of which will still be here in 2025 and even 2050. Our long-term ability to reduce energy use depends critically on the extent to which energy use in these buildings can be reduced when they are renovated. The equipment inside a building, such as the furnace or boiler, water heater, appliances, air conditioner (where present) and lighting is completely replaced over time periods ranging from every few years to every 20–30 years. The building shell – walls, roof, windows and doors – lasts much longer. There are two opportunities to reduce heating and cooling energy use by improving the building envelope: (i) at any time prior to a major renovation, based on simple measures that pay for themselves through reduced energy costs and potential financial support or incentives; and (ii) when renovations are going to be made for other (non-energy) reasons, including replacement of windows and roofs. 6.4.13.1
Conventional retrofits of residential buildings
Cost-effective measures that can be undertaken without a major renovation of residential buildings include: sealing points of air leakage around baseboards, electrical outlets and fixtures, plumbing, the clothes dryer vent, door joists and window joists; weather stripping of windows and doors; and adding insulation in attics, to walls or wall cavities. A Canadian study found that the cost-effective energy savings potential ranges from 25–30% for houses built before the 1940s, to about 12% for houses built in the 1990s (Parker et al., 2000). In a carefully documented retrofit of four representative houses in the York 404
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region of the UK, installation of new window and wooden door frames, sealing of suspended timber ground floors and repair of cracks in plaster reduced the rate of air leakage by a factor of 2.5–3.0 (Bell and Lowe, 2000). This, combined with improved insulation, doors and windows, reduced the heating energy required by an average of 35%. Bell and Lowe (2000) believe that a reduction of 50% could be achieved at modest cost using well-proven (early 1980s) technologies, with a further 30–40% reduction through additional measures. Studies summarized by Francisco et al. (1998) indicate that air-sealing retrofits alone can save an average of 15–20% of annual heating and air conditioning energy use in US houses. Additional energy savings would arise by insulating pipework and ductwork, particularly in unconditioned spaces. Rosenfeld (1999) refers to an ‘AeroSeal’ technique (see Sec. 6.4.2.2) that he estimates is already saving three billion US$/yr in energy costs in the USA. Without proper sealing, homes in the USA lose, on average, about one-quarter of the heating and cooling energy through duct leaks in unconditioned spaces – attics, crawl spaces, basements. In a retrofit of 4003 homes in Louisiana, the heating, cooling and water heating systems were replaced with a ground-source heat pump system. Other measures were installation of attic insulation and use of compact fluorescent lighting and water saving showerheads. Space and hot water heating previously provided by natural gas was supplied instead by electricity (through the heat pump), but total electricity use still decreased by one third (Hughes and Shonder, 1998). External Insulation and Finishing Systems (EIFSs) provide an excellent opportunity for upgrading the insulation and improving the air-tightness of single- and multi-unit residential buildings, as well as institutional and commercial buildings. This is because of the wide range of external finishes that can be applied, ranging from stone-like to a finish resembling aged plaster. A German company manufacturing some of the components used in EIFSs undertook a major renovation of some of its own 1930s multi-unit residential buildings. The EIFSs in combination with other measures achieved a factor of eight measured reduction in heating energy use (see www.3lh. de). An envelope upgrade of an apartment block in Switzerland reduced the heating requirement by a factor of two, while replacing an oil-fired boiler at 85% seasonal average efficiency with an electric heat pump having a seasonal average COP of 3.2 led to a further large decrease in energy use. The total primary energy requirement decreased by about 75% (Humm, 2000). 6.4.13.2
Conventional retrofits of institutional and commercial buildings
There are numerous published studies showing that energy savings of 50 to 75% can be achieved in commercial buildings through aggressive implementation of integrated
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sets of measures. These savings can often be justified in terms of the energy-cost savings alone, although in other cases full justification requires consideration of a variety of less tangible benefits. In the early 1990s, a utility in California sponsored a 10 million US$ demonstration of advanced retrofits. In six of seven retrofit projects, an energy savings of 50% was obtained; in the seventh project, a 45% energy savings was achieved. For Rosenfeld (1999), the most interesting result was not that an alert, motivated team could achieve savings of 50% with conventional technology, but that it was very hard to find a team competent enough to achieve these results. Other, recent examples that are documented in the published literature include: • A realized savings of 40% in heating, plus cooling, plus ventilation energy use in a Texas office building through conversion of the ventilation system from one with constant to one with variable air flow (Liu and Claridge, 1999); • A realized savings of 40% of heating energy use through the retrofit of an 1865 two-story office building in Athens, where low-energy was achieved through some passive technologies that required the cooperation of the occupants (Balaras, 2001); • A realized savings of 74% in cooling energy use in a onestory commercial building in Florida through duct sealing, chiller upgrade and fan controls (Withers and Cummings, 1998); • Realized savings of 50–70% in heating energy use through retrofits of schools in Europe and Australia (CADDET, 1997); • Realized fan, cooling and heating energy savings of 59, 63 and 90% respectively in buildings at a university in Texas; roughly half due to standard retrofit and half due to adjustment of the control-system settings (which were typical for North America) to optimal settings (Claridge et al., 2001). 6.4.13.3
Solar retrofits of residential, institutional and commercial buildings
Solar retrofit performed in Europe under the IEA Solar and Cooling Program achieved savings in space heating of 25–80% (Harvey, 2006, Chapter 14). The retrofit examples described above, while achieving dramatic (35–75%) energy savings, rely on making incremental improvements to the existing building components and systems. More radical measures involve reconfiguring the building so that it can make direct use of solar energy for heating, cooling and ventilation. The now-completed Task 20 of the IEA’s Solar Heating and Cooling (SHC) implementing agreement was devoted to solar retrofitting techniques. Solar renovation measures that have been used are installation of roof- or façade-integrated solar air collectors; roof-mounted or integrated solar DHW heating; transpired solar air collectors, advanced glazing of balconies, external transparent insulation; and construction of a second-skin façade over the original
façade. Case studies are presented in Boonstra and Thijssen (1997), Haller et al. (1997) and Voss (2000a), Voss (2000b) and are summarized in Harvey (2006), Chapter 14). 6.4.14 Trade-offs between embodied energy and operating energy The embodied energy in building materials needs to be considered along with operating energy in order to reduce total lifecycle energy use by buildings. The replacement of materials that require significant amounts of energy to produce (such as concrete and steel) with materials requiring small amounts of energy to produce (such as wood products) will reduce the amount of energy embodied in buildings. Whether this reduces energy use on a lifecycle basis, however, depends on the effect of materials choice on the energy requirements for heating and cooling over the lifetime of the building and whether the materials are recycled at the end of their life (Börjesson and Gustavsson, 2000; Lenzen and Treloar, 2002). For typical standards of building construction, the embodied energy is equivalent to only a few years of operating energy, although there are cases in which the embodied energy can be much higher (Lippke et al., 2004). Thus, over a 50-year time span, reducing the operating energy is normally more important than reducing the embodied energy. However, for traditional buildings in developing countries, the embodied energy can be large compared to the operating energy, as the latter is quite low. In most circumstances, the choice that minimizes operating energy use also minimizes total lifecycle energy use. In some cases, the high embodied energy in high-performance building envelope elements (such as krypton-filled double- or tripleglazed windows) can be largely offset from savings in the embodied energy of heating and/or cooling equipment (Harvey, 2006, Chapter 3), so a truly holistic approach is needed in analysing the lifecycle energy use of buildings. 6.4.15 Trade-offs involving energy-related emissions and halocarbon emissions Emissions of halocarbons from building cooling and refrigeration equipment, heat pumps and foam insulation amount to 1.5 GtCO2-eq at present, compared to 8.6 GtCO2 from buildings (including through the use of electricity) (IPCC/ TEAP, 2005). Emissions due to these uses are projected only to 2015 and are constant or decline in this period. Halocarbon emissions are thus an important consideration. Issues pertaining to stratospheric ozone and climate are comprehensively reviewed in the recent IPCC/TEAP report (IPCC/TEAP, 2005). Halocarbons (CFCs, HCFCs and HFCs) are involved as a working fluid in refrigeration equipment (refrigerators, freezers and cold storage facilities for food), heating and cooling of buildings (heat pumps, air conditioners and chillers) and as an blowing agent used in foam insulation for refrigerators, pipes 405
Residential and commercial buildings
and buildings. All three groups are greenhouse gases. The GWP of HCFCs is generally lower than CFCs. The GWP of HFCs is also generally lower than that of the CFCs, but generally slightly higher than that of the HCFCs. The consumption (production plus imports, minus exports, minus destruction) of CFCs except for critical uses (e.g., medical devices) stopped in 1996 in developed countries, while developing countries have been given to 2010 to eliminate consumption. HCFCs are being phased out, also for reasons of ozone depletion, but will not be completely phased out of production until 2030 in developed countries and 2040 in developing countries. Nevertheless, projected emissions of HCFCs and HFCs (and ongoing emissions from CFC banks) are sufficiently high that scenarios of halocarbon emissions related to buildings in 2015 show almost the same emissions as in 2002 (about 1.5 GtCO2eq. emissions). For the coming decade or longer, the bank of CFCs in the stock of cooling equipment and foams is so large that particular attention needs to be given to recovering these CFCs. Lifetime emissions of refrigerants from cooling equipment, expressed as CO2-eq per unit of cooling, have fallen significantly during the past 30 years. Leakage rates are generally in the order of 3%, but rates as high as 10–15% occur. By 2010, it is expected that HFCs will be the only halocarbon refrigerant to be used in air conditioners and heat pumps manufactured in developed countries. Non-halocarbon refrigerants can entail similar efficiency benefits if the heat pump is fully optimised. Thus, both the performance of the heat pump and the impact of halocarbon emissions need to be considered in evaluating the climatic impact of alternative choices for refrigerants. The climatic impact of air conditioners and most chillers is generally dominated by the energy used to power them. For leakage of HFC refrigerants at rates of 1 to 6%/yr (IPCC/TEAP, 2005) (best practice is about 0.5%/yr) and recovery of 85% of the refrigerant (compared to 70–100% in typical practice) at the end of a 15-year life, refrigerant leakage accounts for only 1 to 5% of the total impact on climate of the cooling equipment to up to 20%, without end-of-life recovery, of the total impact (derived from (IPCC/TEAP, 2005). This demonstrates the importance of end-of-life recovery, which is highly uncertain for HFCs at present. However, for CFC chillers, the high GWP of the refrigerant and the typical high leakage of older CFCbased designs cause the refrigerant to be a significant factor in overall emissions. This demonstrates that emphasis needs to be put on the replacement of CFC chillers in both developed and developing countries for which hydrocarbons are now widely used in EU countries. The energy/HFC relationship for air conditioners does not hold for most large built-up refrigeration systems, such as those found in supermarkets and hypermarkets. Roughly half of the total equivalent emissions from these systems result from the refrigerant, in case an HFC blend is used. Various designs explored in IPCC/TEAP report (IPCC/TEAP, 2005) indicate 406
Chapter 6
that direct refrigerant emissions can drop from 40–60% of the total emissions in a typical system to 15% for improved systems. The value is 0% for systems using hydrocarbon or ammonia refrigerants. Although some designs may incur a slight increase in energy use, total (energy + refrigerant) emissions are nonetheless significantly reduced. For foam insulation blown with halocarbons, the benefit of reduced heating energy use can outweigh the effect of leakage of blowing agent when insulating buildings that were previously either poorly insulated or uninsulated (Ashford et al., 2005). However, for high levels of insulation, the opposite becomes true (Harvey, 2007) without end-of-life recovery of the blowing agent. In general terms, the use of methods such as Life Cycle Climate Performance (LCCP) is essential in evaluating the most appropriate course of action in each situation. 6.4.16 Summary of mitigation options in buildings The key conclusion of section 6.4 is that substantial reductions in CO2 emissions from energy use in buildings can be achieved over the coming years using existing, mature technologies for energy efficiency that already exist widely and that have been successfully used (high agreement, much evidence). There is also a broad array of widely accessible and cost-effective technologies and know-how that can abate GHG emissions in buildings to a significant extent that has not as yet been widely adopted. Table 6.1 summarizes selected key technological opportunities in buildings for GHG abatement in five world regions based on three criteria. Twenty-one typical technologies were selected from those described in section 6.4. As economic and climatic conditions in regions largely determine the applicability and importance of technologies, countries were divided into three economic classes and two climatic types. The three criteria include the maturity of the technology, cost/ effectiveness and appropriateness. Appropriateness includes climatic, technological and cultural applicability. For example, direct evaporative cooling is ranked as highly appropriate in dry and warm climates but it is not appropriate in humid and warm climates. The assessment of some technologies depends on other factors, too. For instance, the heat pump system depends on the energy source and whether it is applied to heating or cooling. In these cases, variable evaluation is indicated in the table.
stage
4
Cost/ effectiveness
ateness stage
Appropri- Technology Cost/ effectiveness
ateness stage
Appropri- Technology effectiveness
Cost/
Warm climate ateness stage
Appropri- Technology effectiveness
Cost/ ateness
Appropri-
Economies in transition, Continental Reference
~ µ
~
~
7
µ
17
8
~
~10
Advance supermarket technologies
conditioners
HC or CO2 air
HC-based domestic refridgerator
~
~
~
25 26
28
µ 27
~
6.4.12
6.4.4.3
6.4.11
6.4.10
~
µ
6.4.7.1
6.4.6
6.4.6
6.4.8
High efficiency lightning (LED)
µ
~
6.4.4.2
6.4.2
6.4.4.1
6.4.3.2
6.4.3.3 6.4.8
6.4.10
~
~
~
24
23
~
~
16
~
~
~
~
~
~
20
19
15
14
High efficiency lightning (FL)
22
21
13
12
6.4.5.1
~
~
11
6.4.3.1
Air to air heat exchanger
PV
District heating & cooling system
Cogeneration
Solar thermal water heater
Direct evaporative cooler
18
~
~
9
~
~
6
Thermal mass to minimize daytime interior temperature peaks
5
~
~
3
2
High-reflectivity bldg. materials
Biomass derived liquid fuel stove
Heat pumps
Passive solar heating
1
6.4.2.2
ateness
Appropri- Technology
OECD
Multiple glazing layers
stage
Cold climate
6.4.2.1
Cost/
effectiveness
Technology
Warm climate
Developing countries
Cold climate
Structural insulation panels
Energy efficiency or emission reduction technology
Table 6.1: Applicability of energy efficiency technologies in different regions. Selected are illustrative technologies, with an emphasis on advanced systems, the rating of which is different between countries
Chapter 6 Residential and commercial buildings
407
408
stage
~
Cost/
effectiveness
Technology ateness
~
stage
Appropri- Technology effectiveness
Cost/
Warm climate ateness
~
stage
Appropri- Technology effectiveness
Cost/
Cold climate ateness
~
stage
effectiveness
Cost/
Warm climate Appropri- Technology
OECD
ateness
~
stage
Appropri- Technology effectiveness
Cost/ ateness
Appropri-
Economies in transition, Continental
6.4.6
6.4.4.2
Reference
Cost/Effectiveness Expensive/Not effective [$$/-] Expensive/Effective [$$/+] Cheap/Effective [$/+] ‘~’ Not available
Stage of technology
Research phase (including laboratory and development) [R]
Demonstration phase [D]
Economically feasible under specific conditions [E]
Mature Market (widespread commercially available without specific governmental support) {M]
No Mature Market (not necessarily available/not necessarily mature market)
~
µ
Visual representation
Evaluation ranks:
‘~’ Not available
Highly appropriate {++]
Appropriate {+]
Not appropriate {-]
Appropriateness
Notes: 1 For heat block type; 2 For Low-E; 3 Limited to ground heat source etc.; 4 For air conditioning; 5 For hot water; 6 For cooling; 7 For hot water; 8 For cooling; 9 Limited to ground heat source, etc.; 10 For cooling; 11 For hot water; 12 For hot water; 13 For cooling; 14 For hot water; 15 For cooling; 16 Limited to ground heat source, etc.; 17 In high humidity region; 18 In arid region; 19 In high humidity region; 20 In arid region; 21 In high humidity region; 22 In arid region; 23 In high humidity region; 24 In arid region; 25 United States; 26 South European Union; 27 United States; 28 South European Union.
Advanced control system based on BEMS
Variable speed drives for pumps and fans
Energy efficiency or emission reduction technology
Cold climate
Developing countries
Table 6.1: Applicability of energy efficiency technologies in different regions. Selected are illustrative technologies, with an emphasis on advanced systems, the rating of which is different between countries
Residential and commercial buildings Chapter 6
Chapter 6
Residential and commercial buildings
6.5 Potential for and costs of greenhouse gas mitigation in buildings The previous sections have demonstrated that there is already a plethora of technological, systemic and management options available in buildings to substantially reduce GHG emissions. This section aims at quantifying the reduction potential these options represent, as well as the costs associated with their implementation. 6.5.1
Recent advances in potential estimations from around the world
Chapter 3 of the TAR (IPCC, 2001) provided an overview of the global GHG emission reduction potential for the residential and commercial sectors, based on the work of IPCC (1996) and Brown et al. (1998). An update of this assessment has been conducted for this report, based on a review of 80 recent studies from 36 countries and 11 country groups, spanning all inhabited continents. While the current appraisal concentrates on new results since the TAR, a few older studies were also revisited if no recent study was located to represent a geopolitical region in order to provide more complete global coverage. Table 6.2 reviews the findings of a selection of major studies on CO2 mitigation potential from various countries around the world that could be characterized in a common framework. Since the studies apply a variety of assumptions and analytical methods, these results should be compared with caution (see the notes for each row, for methodological aspects of such a comparison exercise). According to Table 6.2, estimates of technical potential range from 18% of baseline CO2 emissions in Pakistan (Asian Development Bank, 1998) where only a limited number of options were considered, to 54% in 20109 in a Greek study (Mirasgedis et al., 2004) that covered a very comprehensive range of measures in the residential sector. The estimates of economic potential10 vary from 12% in EU-15 in 201011 (Joosen and Blok, 2001) to 52% in Ecuador in 203012 (FEDEMA, 1999). Estimates of market potential13 range from 14% in Croatia, focusing on four options only (UNFCCC NC1 of Croatia, 2001), to 37% in the USA, where a wide range of policies were appraised (Koomey et al., 2001). Our calculations based on the results of the reviewed studies (see Box 6.1) suggest that, globally, approximately 29% of the projected baseline emissions by 202014 can be avoided costeffectively through mitigation measures in the residential 9 10 11 12 13 14 15
and commercial sectors (high agreement, much evidence). Additionally at least 3% of baseline emissions can be avoided at costs up to 20 US$/tCO2 and 4% more if costs up to 100 US$/ tCO2 are considered. Although due to the large opportunities at low-costs, the high-cost potential has been assessed to a limited extent and thus this figure is an underestimate (high agreement, much evidence). These estimates represent a reduction of approximately 3.2, 3.6 and 4.0 billion tonnes of CO2-eq in 2020, at zero, 20 US$/tCO2 and 100 US$/tCO2, respectively. Due to the limited number of demand-side end-use efficiency options considered by the studies, the omission of non-technological options, the often significant co-benefits, as well as the exclusion of advanced integrated highly efficiency buildings, the real potential is likely to be higher (high agreement, low evidence). While occupant behaviour, culture and consumer choice as well as use of technologies are also major determinants of energy consumption in buildings and play a fundamental role in determining CO2 emissions, the potential reduction through non-technological options is not assessed. These figures are very similar to those reported in the TAR for 2020, indicating the dynamics of GHG reduction opportunities. As previous estimates of additional energy efficiency and GHG reduction potential begin to be captured in a new baseline, they tend to be replaced by the identification of new energy-efficiency and GHG-mitigation options. For comparison with other sectors these potentials have been extrapolated to 2030. The robustness of these figures is significantly lower than those for 2020 due to the lack of research for this year. The extrapolation of the potentials to the year 2030 suggests that, globally, at least 31% of the projected baseline emissions can be mitigated cost-effectively by 2030 in the buildings sector. Additionally at least 4% of baseline emissions can be avoided at costs up to 20 US$/tCO2 and 5% more at costs up to 100 US$/tCO2 (medium agreement, low evidence)15. This mitigation potential would result in a reduction of approximately 4.5, 5.0 and 5.6 billion tonnes of CO2-eq at zero, 20 US$/tCO2 and 100 US$/ tCO2, respectively, in 2030. Both for 2020 and 2030, low-cost potentials are highest in the building sector from all sectors assessed in this report (see Table 11.3). The outlook to the longterm future assuming options in the building sector with a cost up to 25 US$/tCO2 identifies the potential of approximately 7.7 billion tonnes of CO2 in 2050 (IEA, 2006d). The literature on future non-CO2 emissions and potentials for their mitigation have been recently reviewed in the IPCC/TEAP report (2005). The report identifies that there are opportunities to reduce direct emissions significantly through the global application of best practices and recovery methods, with a reduction potential of about 665 million tonnes of CO2-eq of
If the approx. formula of Potential 2020 = 1 - ( 1 - Potential 2010)20/10 is used to extrapolate the potential as percentage of the baseline into the future (2000 is assumed as a start year), this corresponds to approx. 78% CO2 savings in 2020. In this chapter we refer to ‘cost-effective’ or ‘economic’ potential, to remain consistent with the energy-efficiency literature, considering a zero-carbon price. Corresponds to an approx. 22% potential in 2020 if the extrapolation formula is used. Corresponds to an approx. 38% potential in 2020 if the formula is applied to derive the intermediate potential. For definitions of technical, economic, market and enhanced market potential, see Chapter 2 Section 2.4.3.1. The baseline CO2 emission projections were calculated on the basis of the reviewed studies, and are a composite of business-as-usual and frozen efficiency baseline. These are the average figures of the low and high scenario of the potential developed for 2030.
409
410
Reference
Type of potential Description of mitigation scenarios
Jaccard and Associates, 2002
Mirasgedis et al., 2004
DEFRA, 2006
Australian Greenhouse Office, 2005
Kallaste et al., Market 1999
ERI, 2004
Petersdorff et al., 2005
Szlavik et al., 1999
Asian Development Bank, 1998
Canada
Greece
UK
Australia
Estonia
China
New EU Member Statesa)
Hungary
Myanmar
Economic
Economic
Technical
Technical
Enhanced market
Market
Technical
Economic
Technical
Market
Economic
Technical
Joosen and Blok, 2001
EU-15
5 options: shift to CFLs, switch to efficient biomass and LPG cooking stoves, improved kerosene lamps, efficient air conditioners.
25 technological options and measures: building envelope, space heating, hot water supply, ventilation, awareness, lighting, appliances.
Building envelope esp. insulation of walls, roofs, cellar/ground floor, windows with lower U-value; and renewal of energy supply.
Key policies: energy conservation standards, heat price reform, standards & labelling for appliances, energy efficiency projects, etc.
4 insulation measures: 3d window glass, new insulation into houses, renovation of roofs, additional attic insulation.
Fridges and other appliances, air conditioners, water heating, swimming pool equipment, chillers, ballasts, standards, greenlight Australia plan, refrigerated cabinets, water dispensers, standby.
41 options: insulation; low-e double glazing windows; various appliances; heating controls; better IT equipment, more efficient motors, shift to CFLs, BEMS, etc.
14 technological options: fuel switch, controls, insulation, lights, air conditioning and others.
Mainly fuel switch in water and space heating, hot water efficiency and the multi-residential retrofit program in households; landfill gas, building shell efficiency actions and fuel switch in commerce.
25 options: retrofit (insulation); heating systems; new zero & low energy buildings, lights, office equipment & appliances; solar and geo-thermal heat production; BEMS for electricity, space heating and cooling.
Case studies providing information for demand-side measures
Country/ region
Table 6.2: Carbon dioxide emissions reduction potential for residential commercial sectors
3
15
22
62
422
0.4
N.a.
31%
45%
-
23%
2.5% of nation. emis.
15%
24% (res. only)
46
18
25%
54%
24%
12%
21%
Baseline (%)
6
13
22
175
310
Million tCO2
Potential
1. Biomass cooking stoves, 2. Kerosene lamps, 3. CFLs.
1. Individual metering of hot water; 2. Water flow controllers; 3. Retrofitted windows.
1. Roof insulation; 2. Wall insulation; 3. Floor Insulation.
n.a. (not listed in the study)
1. New insulation; 2. Attic insulation; 3. 3d window glass.
1.Standby programs; 2.MEPS for appliances 1999; 3.TVs on-mode.
1. Efficient fridge/ freezers; 2. Efficient chest freezers; 3. Efficient dishwashers.
1. Replacement of central boilers; 2. Use of roof ventilators; 3. Replacement of AC.
n.a. (not listed in the study)
1. Efficient TV and peripheries; 2. Efficient refrigerators & freezers; 3. Lighting Best Practice.
Measures with lowest costs
1. Biomass cooking stoves, 2. LPG cooking stoves, 3. CFLs.
1. Post insulation; 2. Retrofit of windows; 3. Replacement of windows.
1. Window replacement; 2. Wall insulation; 3. Roof insulation.
n.a. (not listed in the study)
1.New insulation; 2.3d window glass; 3.Attic insulation.
1.Packaged airconditioners; 2.Ballast program in 2003; 3.Fluorescent bulbs.
1.Efficient gas boilers; 2.Cavity insulation; 3.Loft insulation.
1.Shell, esp. insulation; 2.Lighting & water heating; 3.Space heating systems.
1.Electricity demand reductions; 2.Commercial landfill gas; 3.Furnaces & shell improvements.
1.Retrofit: insulated windows; 2.Retrofit: wall insulation; 3.BEMS for space heating and cooling.
Measures with highest potential
[1] 10%.
[1] 3%; [5] TY 2030.
[1] 6%; [4] Fr-ef; [5] BY 2006; TY 2015.
[1].N.a.
[1].6%; [5]. BY 1995; TY 2025.
[1].5%; [4]. BL: scenario without measures; [5].BY 2005.
[1].7-5%: R/C; [4].BL: Johnston et al., 2005; [5].BY 2005.
[1].6%; [4].Fr-ef; [5]. TY 2010; [7]. R only.
[1].10%; [5].TY 2010.
[1].4%; [4].Fr-ef.; [5].TY 2010.
Notes
Residential and commercial buildings Chapter 6
Reddy and Balachandra, 2006
Asian Development Bank, 1998
FEDEMA, 1999
Asian Development Bank, 1998
Asian Development Bank, 1998
AIM, 2004
AIM, 2004
AIM, 2004
Gaj and Sadowski, 1997
Izrael et al., 1999
Republic of Korea
Ecuador
Thailand
Pakistan
Indonesia
Argentina
Brazil
Poland
Russia
Reference
India
Country/ region
Table 6.2. Continued.
Economic
Technical
Economic
Downsized thermal generators (boilers and heaters), thermal insulation (improved panels, doors, balconies, windows), heat and hot water meters and controls, hot water distribution devices, electric appliances.
52
182
30
43
4.8
3.3
3.8
10.2
13.5
13%
47%
18%
26%
36%
41%
19%
22%
19%
25%
16%
18%
7 6
13%
6.1
Economic
Technical
13 options: lights in streets, commerce & households, gas boiler controls, appliances, heat meters, thermal insulation for walls and roofs, window tightening & replacement, fuel switch from coal to gas, solar or biomass, DH boilers.
52%
7
31%
17%
20
15
33%
17
Baseline (%)
Potential Million tCO2
5.4
9 Main technological options: energy efficient appliances such as refrigerator and air conditioners, lights (shift from incandescents to fluorescents), kerosene, electricity and gas water heater, kerosene and gas heater, wall and window insulation and others.
Energy efficiency improvements of electric appliances and other end-use devices such as lights, fans, refrigerators, water heaters and improvement of building design.
3 technological programs: lighting (shift to fluorescents), refrigerator (insulation and compressors) and air-conditioning.
6 main options: improvements of appliances, lighting systems, electricity end-uses esp. in rural areas and in the services, solar water heating, public lighting.
7 options: heating - condensing gas boilers, solar hot water systems, insulation standards; cooling - air conditioners; improved lights - shift to fluorescents and CFLs; efficient motors and inverters.
Lighting: mixture of incandescents, fluorescent tubes and CFLs, exchange of traditional kerosene and wood stoves and water heaters for efficient equipment.
Description of mitigation scenarios
Technical
Economic
Technical
Economic
Technical
Economic
Technical
Economic
Technical
Economic
Economic
Market
Type of potential
n.a. (not listed in the study)
1. Efficient street lighting; 2. Improved controls of small gas boilers; 3. Efficient lighting in commerce.
Efficient refrigerator, electricity and gas water heater, kerosene and gas heater, lights, airconditioners (not ranked).
1. Improved lights, 2. Efficient ceiling fans, 3. More efficient refrigerators.
1. Lighting, 2. Efficient refrigerators, 3. Air conditioning.
1. Lights; 2. Electric appliances (esp. rural areas); 3. Electricity end-use in services.
1. Heating: gas boilers, solar hot water, insulation standards; 2. Air conditioners; 3. Inverters & motors.
1. Efficient packages of lighting; 2. Kerosene stoves; 3. Wood stoves.
Measures with lowest costs
[1] 10%; [5] TY 2030.
1. Improved electricity end-uses in rural areas; 2. Electric appliances (esp. in rural areas); 3. Light systems.
n.a. (not listed in the study)
1. Insulation of walls, 2. Improvement of home appliances, 3. Fuel switching from coal to gas, solar and biomass.
1. Efficient refrigerators, 2. Fluorescent lamps, 3. Efficient electric water heater (ranking at negative marginal cost).
1. Efficient ceiling fans, 2. Improved lights, 3. Improved building design.
[1] n.a.; [4] BL: UNFCCC NC3 of Russia, 2002; PNNL & CENEf, 2004; [5] TY 2010.
[1] n.a.; [4] BL: UNFCCC NC3 of Poland, 2001.
[1] 5%; [2] Integrated Assessment; [4] Fr-ef.; [7] R only.
[1] 8%; [5] BY 1998.
[1] 10%; [5] BY 1997; [7] R only.
[1] 8.5%; [5] BY1998.
1. Improved lights; 2. Motors & inverters; 3. Gas boiler RES, solar hot water system, insulation standards.
1. Efficient airconditioning, 2. Efficient refrigerators, 3 Lighting.
[1] n.a.; [5] TY 2010; [7] R only.
Notes
1. Wood stoves, 2. Efficient packages of lighting; 3. Kerosene stoves.
Measures with highest potential
Chapter 6 Residential and commercial buildings
411
412
UNFCCC NC1 of Croatia, 2001
Croatia
Market
Economic
Technical
Type of potential
Electricity savings for not heating purposes (low energy bulbs, more efficient appliances, improved motors), solar energy use increase, thermal insulation improvement.
21 options: light practices; new & retrofits HVAC; stoves, thermal envelope; fuel switch in heaters; standards & labelling; for hot water: improved insulation, heat pumps, efficient use; solar heating.
Description of mitigation scenarios
2
37
41
Koomey et al., 2001
Murakami et al., 2006
Martinsen et al., 2002
USA
Japan
Germany
Technical
Technical
Market
Economic
Two options: fuel switch from coal and oil to natural gas and biomass and heat insulation.
15 options: new and retrofit insulation, double glazing window, home appliances (water & space heating/cooling, lighting, cooking), PVs, solar heating, shift to energy efficient living style, low-carbon electricity generation.
Voluntary labelling, deployment programmes, building codes, new efficiency standards, government procurement, implementation of tax credits, expansion of cost-shared federal R&D expenditures.
Improvement in space and water heating, appliances and lighting, cooling/freezing, airconditioning, cooking, motors, process heat, renewable energies, reduced emissions from electricity generation.
28%
46
26%
37%
898
31
37%
81
n.a. (not listed in the study)
n.a. (not listed in the study)
n.a. (The study did not examine a GHG potential supply cost curve).
n.a. (not listed in the study)
1. Bulbs & appliances; 2. Solar energy use increase; 3. Insulation improvement
1. Energy star equipment; 2. Lighting retrofit; 3. New lighting systems.
Measures with lowest costs
1.Heat insulation; 2.Fuel switch from coal & oil to gas & biomass.
1. Water heater; 2. Space heater; 3. Home appliances.
1. Lighting; 2. Space cooling; 3.Space heating.
[1] n.a.; [5] BY 2002; [7] R only.
[1] n.a.; [7] R only.
[1] 7%; [5] BY 1997.
[1] 3-5%; [5] BY 2005; [7] C includes agriculture.
[1] n.a.
1. Insulation improvement; 2. Solar energy use increase; 3. Bulbs & appliances.
R: 1.Insulation; 2.Heating systems, fuel switch, DH&CHP; C: 1. Energy efficiency, 2. Renewables.
[1] 6%; [4] Fr-ef.; [5] BY 2001; TY 2030.
Notes
1. Hybrid solar water heaters; 2. New building thermal design; 3. New HVAC systems.
Measures with highest potential
Notes specify those parameters which are different from those identified below (the number of a note is the number of the model parameter): a) Hungary, Slovakia, Slovenia, Estonia, Latvia, Lithuania, Poland and the Czech Republic 1. Discount Rate (DR) belongs to the interval [3%; 10%]. 2. Most models are Bottom-up (BU). 3. All models consider CO2. If a study considered GHGs, CO2 only was analysed, if the study assessed C, potential was converted into CO2. 4. Baseline (BL) is Business-as-Usual Scenario (BAU) or similar (Frozen efficiency scenario is abbreviated as fr-ef). 5. Base year (BY) is 2000; Target year (TY) is 2020. 6. Costs covered: cost of incremental reduction, abatement costs, costs of avoided or saved or mitigated CO2, marginal costs. 7. Estimations are made for Residential (R) and commercial (C) sectors in sum.
Lechtenbohmer et al., 2005
New EU Member Statesa)
14%
20%
23%
Baseline (%)
Potential Million tCO2
Studies providing information about both supply and demand-side options not separating them
De Villiers and Matibe, 2000 De Villiers, 2000
Reference
South Africa
Country/ region
Table 6.2. Continued.
Residential and commercial buildings Chapter 6
Chapter 6
Residential and commercial buildings
Box 6.1: Methodology for the global assessment of potentials and costs of CO2 mitigation in buildings This chapter evaluated the potential for GHG mitigation in buildings and associated costs based on the review of existing national and regional potential estimates. For this purpose, over 80 studies containing bottom-up mitigation potential estimates for buildings were identified from 36 countries and 11 country groups covering all inhabited continents. One study (AIM, 2004) covered the entire planet, but it was not suitable for the purposes of this report, as it assessed a very limited number of mitigation options. To allow the comparison of studies in a common framework, their main results and related assumptions were processed and inserted into a database containing the key characteristics of the methods used and results. To eliminate the major effects of different methodological assumptions, only those studies were selected for further analysis whose assumptions fell into a range of common criteria. For instance, studies were only used for further assessment if their discount rates fell in the interval of 3–10%. For studies which did not report their baseline projections, these were taken from the latest available National Communications to the UNFCCC, or other recent related reports. Table 6.2 presents the results of a selection of major mitigation studies meeting such criteria for different parts of the world. For definitions of various mitigation potentials see Chapter 2, Section 2.4.3.1. The next step was to aggregate the results into global and regional potential estimates, as a function of CO2 costs. Only three studies covered a 2030 target year and they were for countries with insignificant global emissions, thus this was only possible for 2020 in the first iteration. Since few studies reported potentials as a function of cost (typically only technical/economic or market potentials were reported), only 17 studies from the remaining subset meeting our other selection criteria could be used. IPCC SRES or WEO scenarios could not be used as a baseline because little information is available for these on the technology assumptions in buildings. In order to make sure the potentials are entirely consistent with the baseline, an average baseline was created from the studies used for the global potential estimates. For the global potential estimates and the baseline construction, the world was split into seven regions16. For each such region, two to four studies were located, thus dividing each region into two to four sub-regions represented by these marker countries in terms of emission growth rates and potential as a percentage of baseline. CO2 baseline emissions in the seven regions were estimated starting with 2000 IPCC A1B and B2 (SRES) data and applying the CO2 growth rates calculated for each region as the population weighted average CO2 baseline growth rates of two to four sub-regions. The baseline projections were estimated for 2000–2020 based on mainly 2020 data from the studies; these trends were prolonged for the period 2020–2030. Since three of the seventeen studies used a frozen efficiency baseline, the baseline used in this chapter can be considered a business-as-usual one with some frozen efficiency elements. The resulting baseline is higher than the B2 (SRES) scenario but lower than A1B (SRES) and WEO scenarios. Analogously, CO2 potentials as a percentage of the baseline in cost categories (US$/tCO2: (<0); (0;20); (20;100)) were calculated based on population weighted average potentials in the sub-regions for each cost category .While the three studies using a frozen efficiency baseline result in a relatively higher potential than in studies using a BAU baseline, this does not compromise the validity of the global potential, since for the regions applying a frozen efficiency baseline, the latter baseline was used in calculating the global total. The results of these estimates are presented in Table 6.3. As mentioned above, only three studies covered the baseline or mitigation potential for 2030. Therefore these figures were derived by extrapolating the 2020 figures to 2030. Since the simple exponential formula used for such extrapolations by other sectors was found to yield disputably high or low results in some cases, a modified exponential function was used which allows regulating the maximum potential considered theoretically achievable for different regions17. The results of the projections are presented in Table 6.4
16 OECD North America, OECD Pacific, Western Europe, Transition Economies, Latin America, Africa and Middle East, and Asia 17 X (t) = Xsaturation –C e –kt (reached from the differential equation: dx/dt = k (Xsaturation –x), saturation illustrates that the closer potential is to this upper limit, the lower potential growth rate is experienced, and the potential does not exceed the maximum judged reasonable. C can be found from the starting conditions (in year 2000); thus if we know the potential in 2020, then: 30 X2020 X2030 = Xsaturation (1 – EXP LN (1 – ) 20 Xsaturation
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direct emissions in 2015, as compared to the BAU scenario. About 40% of this potential is attributed to HFC emission reduction covered by the Kyoto Protocol to the UNFCCC, while HCFCs and CFCs regulated by the Montreal Protocol contribute about 60% of the potential. A key factor determining whether this potential will be realized is the costs associated with the implementation of the measures to achieve the emission reduction. These vary considerably from a net benefit to 300 US$/tCO2-eq. Refrigeration applications and stationary and mobile air conditioning contribute most to global direct GHG emissions. Action in these sub-sectors could therefore have a substantial influence on future emissions of HCFCs and HFCs. The available literature does not contain reliable estimates for non-CO2 mitigation potentials in the long-term future, including the year 2030. Therefore, the 2015 figures can serve as low estimates of the potentials in 2030, taking into account that upcoming progressive policies in many countries have already led to new products with very low non-CO2 emissions as compared to their previous analogues.
6.5.2
Recent advances in estimating the costs of GHG mitigation in buildings
Table 6.3 below and Table 6.4 provide information on the GHG abatement potentials in buildings as a function of costs and world regions for 2020 (Table 6.3) and for 2030 (Table 6.4). These demonstrate that the majority of measures for CO2 abatement in buildings are cost-effective. The table also demonstrates that measures to save electricity in buildings typically offer larger and cheaper options to abate CO2 emissions than measures related to fuel savings. This is especially true for developing countries located in warmer regions, which have less need for space and water heating. 6.5.3
Supply curves of conserved carbon dioxide
CO2 conservation supply curves relate the quantity of CO2 emissions that can be reduced by certain technological or other measures to the cost per unit CO2 savings (Sathaye and Meyers,
Table 6.3: CO2 mitigation potential projections in 2020 as a function of CO2 cost Baseline emissions in 2020 World regions
CO2 mitigation potentials as share of the baseline CO2 emission projections in cost categories in 2020 (costs in US$/tCO2-eq)
CO2 mitigation potentials in absolute values in cost categories in 2020, GtCO2 (costs in US$/tCO2-eq)
(GtCO2-eq)
<0
0-20
20-100
<100
<0
0-20
20-100
<100
11.1
29%
3%
4%
36%
3.2
0.35
0.45
4.0
OECD (-EIT)
4.8
27%
3%
2%
32%
1.3
0.10
0.10
1.6
EIT
1.3
29%
12%
23%
64%
0.4
0.15
0.30
0.85
Non-OECD
5.0
30%
2%
1%
32%
1.5
0.10
0.05
1.6
Globe
Table 6.4: Extrapolated CO2 mitigation potential in 2030 as a function of CO2 cost, GtCO2 Potential in different cost categories
Mitigation option
Region
Baseline projections in 2030
Electricity savingsa
OECD
Fuel savings
Total
Potential at costs at below 100 US$/tCO2-eq
<0 US$/tCO2
0-20 US$/tCO2
20-100 US$/ tCO2
<0 US$/tC
0-73 US$/tC
73-367 US$/tC
Low
High
3.4
0.75
0.95
0.85
0.0
0.0
EIT
0.4
0.15
0.20
0.20
0.0
0.0
Non-OECD/ EIT
4.5
1.7
2.4
1.9
0.1
0.1
OECD
2.0
1.0
1.2
0.85
0.2
0.1
EIT
1.0
0.55
0.85
0.20
0.2
0.3
Non-OECD/ EIT
3.0
0.70
0.80
0.65
0.1
0.0
OECD
5.4
1.8
2.2
1.7
0.2
0.1
EIT
1.4
0.70
1.1
0.40
0.2
0.3
Non-OECD/ EIT
7.5
2.4
3.2
2.5
0.1
0.0
14.3
4.8
6.4
4.5
0.5
0.7
Global
Note: a) The absolute values of the potentials resulting from electricity savings in Table 6.4 and Table 11.3 do not coincide due to application of different baselines. Table 6.4 uses the baseline constructed on the basis of the reviewed studies while Table 11.3 applies WEO 2004 baseline (IEA, 2004e) to calculate CO2 emission reductions from electricity savings. The potential estimates as a percentage of the baseline are the same in both cases. Also Table 11.3 excludes the share of emission reductions which is already taken into account by the energy supply sector, while Table 6.4 does not separate this potential.
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6.5.4
1995). The measures, or packages of measures, are considered in order of growing marginal CO2 abatement cost, therefore forming a ‘supply curve’ for the commodity of CO2 reduction.
From a policy-design perspective, it is important to understand which technologies/end-uses entail the lowest unit abatement costs for society, as well as which ones offer the largest abatement potential. This section reviews the most attractive mitigation options in terms of overall potential. Both Table 6.4 and Table 11.3 in Chapter 11 demonstrate that CO2saving options are largest from fuel use in developed countries and countries in transition due to their more northern locations and, thus, larger potential for heat-saving measures. Conversely, electricity savings constitute the largest potential in developing countries located in the south, where the majority of emissions in the buildings sector are associated with appliances and cooling. This distribution of the potential also explains the difference in mitigation costs between developing and developed countries. The shift to more efficient appliances quickly pays back, while building shell retrofits and fuel switching, together providing approximately half of the potential in developed countries, are more expensive.
Figure 6.4 depicts the potentials for CO2 abatement as a function of costs for eight selected recent detailed studies from different world regions. The steepness of the curves, that is the rate at which the costs of the measures increase as more of the potential is captured, varies substantially by country and by study. While the shape of each supply curve is profoundly influenced by the underlying assumptions and methods used in the study, the figure attests that opportunities for cost-effective and low-cost CO2 mitigation in buildings are abundant in each world region. All eight studies covered here identified measures at negative costs. The supply curves of developing countries and economies in transition are characterized by a flat slope and lie, in general, lower than the curves of developed countries. The flat slope justifies the general perception (for instance, which provided the main rationale for the Kyoto Flexibility Mechanisms) that there is a higher abundance of ‘low-hanging fruit’ in these countries. More concretely, the net costs of GHG mitigation in buildings in these countries do not grow rapidly even over 30–50% of emissions reductions. For developed countries, the baseline scenario assumes that many of the lowcost opportunities are already captured due to progressive policies in place or in the pipeline.
40
Most attractive measures in buildings
While it is impossible to draw universal conclusions regarding individual measures and end-uses, Table 6.2 attests that efficient lighting technologies are among the most promising measures in buildings, in terms of both cost-effectiveness and size of potential savings in almost all countries. The IEA
US$/tCO2 EU-15
20
UK
South Korea
0
Greece
-20
Pakistan
-40 Thailand
-60
Poland
Hungary
-80 -100 -120 -140 0
5
10
15
20
25
30 35 40% Potential as % of the baseline
Figure 6.4: Supply curves of conserved CO2 for commercial and residential sectora in 2020b for different world regions Notes: a) Except for the UK, Thailand and Greece, for which the supply curves are for the residential sector only. b) Except for EU-15 and Greece, for which the target year is 2010 and Hungary, for which the target year is 2030. Each step on the curve represents a type of measure, such as improved lighting or added insulation. The length of a step on the ‘X’ axis shows the abatement potential represented by the measure, while the cost of the measure is indicated by the value of the step on the ‘Y’ axis. Sources for data: Joosen and Blok, 2001; Asian Development Bank, 1998; De Villiers and Matibe, 2000; De Villiers, 2000; Szlavik et al., 1999; DEFRA, 2006; Mirasgedis et al., 2004; Gaj and Sadowski, 1997.
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(2006b) estimates that by 2020, approximately 760 Mt of CO2 emissions can be abated by the adoption of least life-cycle cost lighting systems globally, at an average cost of US$–161/tCO2. In developing countries, efficient cooking stoves rank second, while the second-place measures differ in the industrialized countries by climatic and geographic region. Almost all studies examining economies in transition (typically in cooler climates) have found heating-related measures to be most cost-effective, including insulation of walls, roofs, windows and floors, as well as improved heating controls for district heat. In developed countries, appliance-related measures are typically identified as the most cost-effective, with cooling-related equipment upgrades ranking high in the warmer climates. In terms of the size of savings, improved insulation and district heating in the colder climates and efficiency measures related to space conditioning in the warmer climates come first in almost all studies,18 along with cooking stoves in developing countries. Other measures that rank high in terms of savings potential are solar water heating, efficient lighting and efficient appliances, as well as building energy management systems. 6.5.5
Energy and cost savings through use of the Integrated Design Process (IDP)
Despite the usefulness of supply curves for policy-making, the methods used to create them rarely consider buildings as integrated systems; instead, they focus on the energy savings potential of incremental improvements to individual energyusing devices. As demonstrated in the first part of this chapter, integrated building design not only can generate savings that are greater than achievable through individual measures, but can also improve cost-effectiveness. This suggests that studies relying solely on component estimates may underestimate the abatement potential or overestimate the costs, compared with a systems approach to building energy efficiency. Recent published analyses show that, with an integrated approach, (i) the cost of saving energy can go down as the amount of energy saved goes up, and (ii) highly energy-efficient buildings can cost less than buildings built according to standard practice (Harvey, 2006; Chapter 13).
6.6 Co-benefits of GHG mitigation in the residential and commercial sectors Co-benefits of mitigation policies should be an important decision element for decision-makers in both the residential and commercial sectors. Although these co-benefits are often not quantified, monetized, or perhaps even identified by the decision-makers or economic modellers (Jochem and Madlener, 2003), they can still play a crucial role in making GHG
Chapter 6
emissions mitigation a higher priority. This is especially true in less economically advanced countries, where environmentalism – and climate change specifically – may not have a strong tradition or a priority role in either the policy agenda or the daily concerns of citizens. In these circumstances, every opportunity for policy integration can be of value in order to reach climate change mitigation goals. 6.6.1
Reduction in local/regional air pollution
Climate mitigation through energy efficiency in the residential and commercial sectors will improve local and regional air quality, particularly in large cities, contributing to improved public health (e.g., increased life expectancy, reduced emergency room visits, reduced asthma attacks, fewer lost working days) and avoidance of structural damage to buildings and public works. As an example in China, replacement of residential coal burning by large boiler houses providing district heating is among the abatement options providing the largest net benefit per tonne of CO2 reduction, when the health benefits from improved ambient air conditions are accounted for (Mestl et al., 2005). A study in Greece (Mirasgedis et al., 2004) found that the economic GHG emissions abatement potential in the residential sector could be increased by almost 80% if the co-benefits from improved air quality are taken into account. Beyond the general synergies between improved air quality and climate change mitigation described in Chapter 11 (see Section 11.8.1), some of the most important co-benefits in the households of developing countries are due to reduced indoor air pollution through certain mitigation measures, discussed in sections 6.6.2 and 6.1.1. 6.6.2
Improved health, quality of life and comfort
In the least developed countries, one of the most important opportunities for achieving GHG mitigation as well as sustainable development in buildings is to focus on the healthrelated benefits of clean domestic energy services, including safe cooking. Indoor air pollution is a key environmental and public health peril for countless of the world’s poorest, most vulnerable people. Approximately three billion people worldwide rely on biomass (wood, charcoal, crop residues and dung) and coal to meet their household cooking and heating energy needs (ITDG, 2002). Smoke from burning these fuels contributes to acute respiratory infections in young children and chronic obstructive pulmonary disease in adults. These health problems are responsible for nearly all of the 2.2 million deaths attributable to indoor air pollution each year, over 98% of which are in developing countries (Gopalan and Saksena, 1999; Smith et al., 2004), (See Box 6.2). In addition, women and children also bear the brunt of the work of collecting biomass fuel. Clean-burning cooking stoves not only save substantial amounts of GHG emissions, but also prevent many of these
18 Note that several studies covered only electricity-related measures, and thus excluded some heating options.
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Box 6.2: Traditional biomass-based cooking has severe health effects In South Africa, children living in homes with wood stoves are almost five times more likely than others to develop respiratory infections severe enough to require hospitalization. In Tanzania, children younger than five years who die of acute respiratory infection are three times more likely than healthy children to have been sleeping in a room with an open cooking stove. In the Gambia, children carried on their mothers’ backs as the mothers cook over smoky stoves contract pneumonia at a rate 2.5 times higher than unexposed children. In Colombia, women exposed to smoke during cooking are over three times more likely than others to suffer from chronic lung disease. In Mexico, urban women who use coal for cooking and heating over many years are subject to a risk of lung cancer two to six times higher than women who use gas. Rural coal smoke exposure can increase lung cancer risks by a factor of nine or more. In India, smoke exposure has been associated with a 50% increase in stillbirths. Cleaner-burning improved cooking stoves (ICS), outlined in the previous sections of this chapter, help address many of the problems associated with traditional cooking methods. The benefits derived from ICS are: 1) reduced health risks for women and children due to improved indoor air quality; 2) reduced risks associated with fuel collection; 3) cost-effective and efficient energy use, which eases the pressure on the natural biomass resource; 4) a reduction in the amount of money spent on fuel in urban areas; and 5) a reduction in fuel collection and cooking time, which translates into an increase in time available for other economic and developmental activities. Source: UN, 2002
health problems and provide many other benefits identified in Box 6.2. In developed countries, the diffusion of new technologies for energy use and/or savings in residential and commercial buildings contributes to an improved quality of life and increases the value of buildings. Jakob (2006) lists examples of this type of co-benefit, such as improved thermal comfort (fewer cold surfaces such as windows) and the substantially reduced level of outdoor noise infiltration in residential or commercial buildings due to triple-glazed windows or high-performance wall and roof insulation. At noisy locations, an improvement of 10–15 dB could result in gross economic benefits up to the amount of 3–7% of the rental income from a building (Jakob, 2006). Lastly, better-insulated buildings eliminate moisture problems associated with, for example, thermal bridges and damp basements and thus reduce the risk of mould build-up and associated health risks. 6.6.3
Improved productivity
There is increasing evidence that well-designed, energy efficient buildings often have the co-benefits of improving occupant productivity and health (Leaman and Bordass, 1999; Fisk, 2000; Fisk, 2002). Assessing these productivity gains is difficult (CIBSE (The Chartered Institution of Building Services Engineers), 1999) but in a study of 16 buildings in the UK, occupants estimated that their productivity was influenced by the environment by between –10% and +11% (Leaman and Bordass, 1999).
The implementation of new technologies for GHG emissions mitigation achieves substantial learning and economies of scale, resulting in cost reductions. Jacob and Madlener (2004) analyzed the technological progress and marginal cost developments for energy efficiency measures related to the building envelope using data for the time period 1975 to 2001 in Switzerland. The analysis yields technical progress factors of around 3% per annum for wall insulation and 3.3% per annum for double glazing windows, while real prices decreases of 0.6% since 1985 for facades and 25% over the last 30 years for double glazing windows (Jacob and Madlener, 2004). 6.6.4
Employment creation and new business opportunities
Most studies agree that energy-efficiency investments will have positive effects on employment, directly by creating new business opportunities and indirectly through the economic multiplier effects of spending the money saved on energy costs in other ways (Laitner et al., 1998; Jochem and Madlener, 2003). Providing energy-efficiency services has proven to be a lucrative business opportunity. Experts estimate a market opportunity of € 5–10 billion in energy service markets in Europe (Butson, 1998). The data on energy service company (ESCO) industry revenues in Section 6.8.3.5 demonstrates that the energy services business appears to be both a very promising and a quickly growing business sector worldwide. The European Commission (2005) estimates that a 20% reduction in EU energy consumption by 2020 can potentially create (directly or indirectly) as many as one million new jobs in Europe, especially in the area of semi-skilled labour in the buildings trades (Jeeninga et al., 1999; European Commission, 2003). 417
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6.6.5
Improved social welfare and poverty alleviation
Improving residential energy efficiency helps households cope with the burden of paying utility bills and helps them afford adequate energy services. One study estimated that an average EU household could save € 200–1000 (US$ 248– 1240) in utility costs through cost-effective improvements in energy efficiency (European Commission, 2005). Reducing the economic burden of utility bills is an important co-benefit of energy efficiency for less affluent households. This is especially true in former communist countries and others (e.g., in Asia and Latin America) where energy subsidies have been removed and energy expenditures are a major burden for much of the population (Ürge-Vorsatz et al., 2006). In economies in transition, this situation provides an opportunity to redirect those social programmes aimed at compensating for increasing energy costs towards energy-efficiency efforts. In this way resources can be invested in long-term bill reduction through energy efficiency instead of one-time subsidies to help pay current utility bills (Ürge-Vorsatz and Miladinova, 2005). Fuel poverty, or the inability to afford basic energy services to meet minimal needs or comfort standards, is also found in even the wealthiest countries. In the UK in 1996, about 20% of all households were estimated to live in fuel poverty. The number of annual excess winter deaths, estimated by the UK Department of Health at around 30 thousand annually between 1997 and 2005, can largely be attributed to inadequate heating (Boardman, 1991; DoH (UK Department of Health), 2000). Improving energy efficiency in these homes is a major component of strategies to eradicate fuel poverty. In developing countries, energy-efficient household equipment and low-energy building design can contribute to poverty alleviation through minimizing energy expenditures, therefore making more energy services affordable for lowincome households (Goldemberg, 2000). Clean and efficient utilization of locally available renewable energy sources reduces or replaces the need for energy and fuel purchases, increasing the access to energy services. Therefore, sustainable development strategies aimed at improving social welfare go hand-in-hand with energy efficiency and renewable energy development. 6.6.6
Energy security
Additional co-benefits of building-level GHG mitigation include improved energy security and system reliability (IEA, 2004f), discussed in more detail in Chapter 4. Improving end-use energy efficiency is among the top priorities on the European Commission’s agenda to increase energy security, with the recognition that energy efficiency is likely to generate additional macro-economic benefits because reduced energy imports will improve the trade balances of importing countries (European Commission, 2003). 418
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6.6.7
Summary of co-benefits
In summary, investments in residential and commercial building energy efficiency and renewable energy technologies can yield a wide spectrum of benefits well beyond the value of saved energy and reduced GHG emissions. Several climate mitigation studies focusing on the buildings sector maintain that, if co-benefits of the various mitigation options are included in the economic analysis, their economic attractiveness may increase considerably – along with their priority levels in the view of decision-makers (Jakob et al., 2002; Mirasgedis et al., 2004; Banfi et al., 2006). Strategic alliances with other policy fields, such as employment, competitiveness, health, environment, social welfare, poverty alleviation and energy security, can provide broader societal support for climate change mitigation goals and may improve the economics of climate mitigation efforts substantially through sharing the costs or enhancing the dividends (European Commission, 2005). In developing countries, residential and commercial-sector energy efficiency and modern technologies to utilize locally available renewable energy forms, can form essential components of sustainable development strategies.
6.7 Barriers to adopting building technologies and practices that reduce GHG emissions The previous sections have shown the significant costeffective potential for CO2 mitigation through energy efficiency in buildings. The question often arises: If these represent profitable investment opportunities, or energy cost savings foregone by households and businesses, why are these opportunities not pursued? If there are profits to be made, why do markets not capture these potentials? Certain characteristics of markets, technologies and end-users can inhibit rational, energy-saving choices in building design, construction and operation, as well as in the purchase and use of appliances. The Carbon Trust (2005) suggests a classification of these barriers into four main categories: financial costs/benefits; hidden costs/benefits; real market failures; and behavioural/ organizational non-optimalities. Table 6.5 gives characteristic examples of barriers that fall into these four main categories. The most important among them that pertain to buildings are discussed below in further detail. 6.7.1
Limitations of the traditional building design process and fragmented market structure
One of the most significant barriers to energy-efficient building design is that buildings are complex systems. While the typical design process is linear and sequential, minimizing energy use requires optimizing the system as a whole by systematically addressing building form, orientation, envelope,
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Table 6.5: Taxonomy of barriers that hinder the penetration of energy efficient technologies/practices in the buildings sector Barrier categories
Definition
Examples
Financial costs/ benefits
Ratio of investment cost to value of energy savings
Higher up-front costs for more efficient equipment Lack of access to financing Energy subsidies Lack of internalization of environmental, health and other external costs
Hidden costs/benefits
Cost or risks (real or perceived) that are not captured directly in financial flows
Costs and risks due to potential incompatibilities, performance risks, transaction costs etc. Poor power quality, particularly in some developing countries
Market failures
Market structures and constraints that prevent the consistent trade-off between specific energy-efficient investment and the energy saving benefits
Limitations of the typical building design process Fragmented market structure Landlord/tenant split and misplaced incentives Administrative and regulatory barriers (e.g., in the incorporation of distributed generation technologies) Imperfect information
Behavioural and organizational nonoptimalities
Behavioural characteristics of individuals and organizational characteristics of companies that hinder energy efficiency technologies and practices
Tendency to ignore small opportunities for energy conservation Organizational failures (e.g., internal split incentives) Non-payment and electricity theft Tradition, behaviour, lack of awareness and lifestyle Corruption
Source: Carbon Trust, 2005.
glazing area and a host of interaction and control issues involving the building’s mechanical and electrical systems. Compounding the flaws in the typical design process is fragmentation in the building industry as a whole. Assuring the long-term energy performance and sustainability of buildings is all the more difficult when decisions at each stage of design, construction and operation involve multiple stakeholders. This division of responsibilities often contributes to suboptimal results (e.g., under-investment in energy-efficient approaches to envelope design because of a failure to capitalize on opportunities to down-size HVAC equipment). In Switzerland, this barrier is being addressed by the integration of architects into the selection and installation of energy-using devices in buildings (Jefferson, 2000); while the European Directive on the Energy Performance of Buildings in the EU (see Box 6.3) aims to bring engineers in at early stages of the design process through its whole-building, performance-based approach. 6.7.2
Misplaced incentives
Misplaced incentives, or the agent-principal barrier takes place when intermediaries are involved in decisions to purchase energy-saving technologies, or agents responsible for investment decisions are different from those benefiting from the energy savings, for instance due to fragmented institutional organizational structures. This limits the consumer’s role and often leads to an under-emphasis on investments in energy efficiency. For example, in residential buildings, landlords often provide the AC equipment and major appliances and decide on building renovation, while the tenant pays the energy bill. As a result, the landlord is not likely to invest in energy efficiency, since he or she is not the one rewarded for the investment (Scott,
1997; Schleich and Gruber, 2007). Decisions about the energy features of a building (e.g., whether to install high-efficiency windows or lighting) are often made by agents not responsible for the energy bills or not using the equipment, divorcing the interests of the builder/investor and the occupant. For example, in many countries the energy bills of hospitals are paid from central public funds while investment expenditures must come either from the institution itself or from the local government (Rezessy et al., 2006). Finally, the prevailing selection criteria and fee structures for building designers may emphasize initial costs over life-cycle costs, hindering energy-efficiency considerations (Lovins, 1992; Jones et al., 2002). 6.7.3
Energy subsidies, non-payment and theft
In many countries, electricity historically has been subsidized to residential customers (and sometimes to commercial or government customers as well), creating a disincentive for energy efficiency. This is particularly the case in many developing countries and historically in Eastern Europe and the former Soviet Union – for example widespread fuel poverty in Russia has driven the government to subsidize energy costs (Gritsevich, 2000). Energy pricing that does not reflect the longterm marginal costs of energy, including direct subsidies to some customers, hinders the penetration of efficient technologies (Alam et al., 1998). However, the abrupt lifting of historically prevailing subsidies may also have adverse effects. After major tariff increases, non-payment has been reported to be a serious issue in some countries. In the late 1990s, energy bill collection rates in Albania, Armenia and Georgia were around 60% of billings. Besides non-payment, electricity theft has been occurring on a 419
Residential and commercial buildings
large scale in many countries – estimates show that distribution losses due to theft are as high as 50% in some states in India (New Delhi, Orissa and Jammu-Kashmir) (EIA (Energy Information Administration), 2004). Even in the United States, it has been estimated to cost utilities billions of dollars each year (Suriyamongkol, 2002). The failure of recipients to pay in full for energy services tends to induce waste and discourage energy efficiency. 6.7.4
Regulatory barriers
A range of regulatory barriers has been shown to stand in the way of building-level distributed generation technologies such as PV, reciprocating engines, gas turbines and fuel cells (Alderfer et al., 2000). In many countries, these barriers include variations in environmental permitting requirements, which impose significant burdens on project developers. Similar variations in metering policies cause confusion in the marketplace and represent barriers to distributed generation. Public procurement regulations often inhibit the involvement of ESCOs or the implementation of energy performance contracts. Finally, in some countries the rental market is regulated in a way that discourages investments in general and energy-efficient investments in particular.
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6.7.6
Information about energy-efficiency options is often incomplete, unavailable, expensive and difficult to obtain or trust. In addition, few small enterprises in the building industry have access to sufficient training in new technologies, new standards, new regulations and best practices. This insufficient knowledge is compounded by uncertainties associated with energy price fluctuations (Hassett and Metcalf, 1993). It is particularly difficult to learn about the performance and costs of energy-efficient technologies and practices, because their benefits are often not directly observable. For example, households typically receive an energy bill that provides no breakdown of individual end-uses and no information on GHG emissions, while infrequent meter readings (e.g., once a year, as is typical in many EU countries) provide insufficient feedback to consumers on their energy use and on the potential impact of their efficiency investments. Trading off energy savings against higher purchase prices for many energy-efficient products involves comparing the time-discounted value of the energy savings with the present cost of the equipment – a calculation that can be difficult for purchasers to understand and compute. 6.7.7
6.7.5
Small project size, transaction costs and perceived risk
Many energy-efficiency projects and ventures in buildings are too small to attract the attention of investors and financial institutions. Small project size, coupled with disproportionately high transaction costs – these are costs related to verifying technical information, preparing viable projects and negotiating and executing contracts – prevent some energy-efficiency investments. Furthermore, the small share of energy expenditures in the disposable incomes of affluent population groups, and the opportunity costs involved with spending the often limited free time of these groups on finding and implementing the efficient solutions, severely limits the incentives for improved efficiency in the residential sector. Similarly, small enterprises often receive higher returns on their investments into marketing or other business-related activities than investing their resources, including human resources, into energy-related activities. Conservative, asset-based lending practices of financial institutions, a limited understanding of energy-efficiency technologies on the part of both lenders and their consumers, lack of traditions in energy performance contracting, volatile prices for fuel (and in some markets, electricity), and small, non-diversified portfolios of energy projects all increase the perception of market and technology risk (Ostertag, 2003; Westling, 2003; Vine, 2005). As discussed in Section 6.8 below, policies can be adopted that can help reduce these transaction costs, thus improving the economics and financing options for energy-efficiency investments.
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Culture, behaviour, lifestyle and the rebound effect
Another broad category of barriers stems from the cultural and behavioural characteristics of individuals. The potential impact of lifestyle and tradition on energy use is most easily seen by cross-country comparisons. For example, dishwasher usage was 21% of residential energy use in UK residences in 1998 but 51% in Sweden (European Commission, 2001). Cold water is traditionally used for clothes washing in China (Biermayer and Lin, 2004) whereas hot water washing is common in Europe. Similarly, there are substantial differences among countries in how lighting is used at night, room temperatures considered comfortable, preferred temperatures of food or drink, the operating hours of commercial buildings, the size and composition of households, etc. (IEA, 1997; Chappells and Shove, 2004). Variation across countries in quantity of energy used per capita, which is large both at economy and household levels (IEA, 1997), can be explained only partly by weather and wealth; this is also appropriately attributed to different lifestyles. Even in identical houses with the same number of residents, energy consumption has been shown to differ by a factor of two or more (Socolow, 1978). Studies aimed at understanding these issues suggest that while lifestyle, traditions and culture can act as barriers, retaining and supporting lower-consuming lifestyles may also be effective in constraining GHG emissions (e.g., EEA, 2001). The ‘rebound effect’ has often been cited as a barrier to the implementation of energy-efficiency policies. This takes place when increased energy efficiency is accompanied by increased demand for energy services (Moezzi and Diamond, 2005). The
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literature is divided about the magnitude of this effect (Herring, 2006). 6.7.8
6.8.1
Policies and programmes aimed at building construction, retrofits, and installed equipment and systems
Other barriers 6.8.1.1
Due to space limitations, not all barriers to energy efficiency identified in Table 6.5 can be detailed here. Other important barriers in the buildings sector include the limited availability of capital and limited access to capital markets of low-income households and small businesses, especially in developing countries (Reddy, 1991); limited availability of energy-efficient equipment along the retail chain (Brown et al., 1991); the case of poor power quality in some developing countries interfering with the operation of the electronics needed for energy efficient end-use devices (EAP UNDP, 2000); and the inadequate levels of energy services (e.g., insufficient illumination levels in schools, or unsafe wiring) in many public buildings in developing countries and economies in transition. This latter problem can severely limit the cost-effectiveness of efficiency investments, since a proposed efficiency upgrade must also address these issues, offsetting most or all of the energy and cost savings associated with improved efficiency and in turn make it difficult to secure financing or pay back a loan from energy cost savings.
6.8 Policies to promote GHG mitigation in buildings Preceding sections have demonstrated the high potential for reducing GHG emissions in buildings through cost-effective energy-efficiency measures and distributed (renewable) energy generation technologies. The previous section has demonstrated that even the cost-effective part of the potential is unlikely to be captured by markets alone, due to the high number of barriers. Although there is no quantitative or qualitative evidence in the literature, it is possible that barriers to the implementation of economically attractive GHG reduction measures are the most numerous and strongest in the building sector, especially in households. Since policies can reduce or eliminate barriers and associated transaction costs (Brown, 2001), special efforts targeted at removing the barriers in the buildings sector may be especially warranted for GHG mitigation efforts. Sections 6.8.1–6.8.5 describe a selection of the major instruments summarized in Table 6.6 that complement the more general discussion of Chapter 13, with a focus on policy tools specific to or specially applied to buildings. The rest of Table 6.6 is discussed in Section 6.8.5.
Building codes
Building regulations originally addressed questions related to safety and the protection of occupants. Oil price shocks in the 1970s led most OECD countries to extend their regulations to include energy efficiency. Nineteen out of twenty OECD countries surveyed have such energy standards and regulations, although coverage varies among countries (OECD, 2003). Building energy codes may be classified as follows: 1) Overall performance-based codes that require compliance with an annual energy consumption level or energy cost budget, calculated using a standard method. This type of code provides flexibility but requires well-trained professionals for implementation; 2) Prescriptive codes that set separate performance levels for major envelope and equipment components, such as minimum thermal resistance of walls, maximum window heat loss/gain and minimum boiler efficiency. There are also examples of codes addressing electricity demand. Several cantons in Switzerland specify maximum installed electric loads for lighting ventilation and cooling in new commercial buildings (SIA, 2006); and 3) A combination of an overall performance requirement plus some component performance requirements, such as wall insulation and maximum window area. Energy codes are often considered to be an important driver for improved energy efficiency in new buildings. However, the implementation of these codes in practice needs to be well prepared and to be monitored and verified. Compliance can be difficult to enforce and varies among countries and localities (XENERGY, 2001; City of Fort Collins, 2002; OECD, 2003; Ürge-Vorsatz et al., 2003). Prescriptive codes are often easier to enforce than performance-based codes (Australian Greenhouse Office, 2000; City of Fort Collins, 2002; Smith and McCullough, 2001). However, there is a clear trend in many countries towards performance-based codes that address the overall energy consumption of the buildings. This trend reflects the fact that performance-based policies allow optimization of integrated design and leave room for the creativity of designers and innovative technologies. However, successful implementation of performance-based codes requires education and training – of both building officials and inspectors – and demonstration projects showing that the building code can be achieved without much additional cost and without technical problems (Joosen, 2006). New software-based design and education tools, including continuous e-learning tools, are examples of tools that can provide good design techniques, continuous learning by professionals, easier inspection methods and virtual testing of new technologies for construction and building systems.
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Public policies in many countries are also increasingly addressing energy efficiency in existing buildings. For instance, the EU Commission introduced the Directive on the Energy Performance of Buildings in 2003 (see Box 6.3), which standardized and strengthened building energy-efficiency requirements for all EU Member States. To date, most codes for existing buildings include requirements for minimum levels of performance of the components used to retrofit building elements or installations. In some countries, the codes may even prohibit the use of certain technologies – for example Sweden’s prohibition of direct electric resistance heating systems, which has led to the rapid introduction of heat pumps in the last five years. Finally, the EU Directive also mandated regular inspection and maintenance of boilers and space conditioning installations in existing buildings (see Box 6.3). According to the OECD (2003), there is still much room for further upgrading building energy-efficiency codes throughout the OECD member countries. To remain effective, these codes have to be regularly upgraded as technologies improve and costs of energy-efficient features and equipment decline. Setting flexible (e.g., performance-based) codes can help keep compliance costs low and may provide more incentives for innovation. 6.8.1.2
Building certification and labelling systems
The purpose of building labelling and certification is to overcome barriers relating to the lack of information, the high transaction costs, the long lifetime of buildings and the problem of displaced incentives between the builder and buyer,
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or between the owner and tenant. Certification and labelling schemes can be either mandatory or voluntary. With the introduction of the EU Directive on the Energy Performance of Buildings (see Box 6.3), building certification is to be instituted throughout Europe. Voluntary certification and/or labelling systems have also been developed for building products such as windows, insulation materials and HVAC components in North America, the EU and a few other countries (McMahon and Wiel, 2001; Menanteau, 2001). The voluntary Energy Star Buildings rating and Energy Star Homes label in the USA and the NF-MI voluntary certificate for houses in France have proven to be effective in ensuring compliance with energy code requirements and sometimes in achieving higher performance levels (Hicks and Von Neida, 1999). Switzerland has developed the ‘Minergie’ label for new buildings that have a 50% lower energy demand than buildings fulfilling the mandatory requirements; such buildings typically require roughly 6% additional investment costs (OPET Network, 2004). Several local governments in Japan apply the Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) (IBEC, 2006). The Australian city of Canberra (ACT) has a requirement for all houses to be energy-efficiency rated on sale. The impact on the market has been to place a financial value on energy efficiency through a well-informed marketplace (ACT, 2006). 6.8.1.3
Education, training and energy audit programmes
Lack of awareness of energy-savings opportunities among practicing architects, engineers, interior designers and
Box 6.3: The European Directive on the Energy Performance of Buildings One of the most advanced and comprehensive pieces of regulation targeted at the improvement of energy efficiency in buildings is the new European Union Directive on the Energy Performance of Buildings (European Commission, 2002). The Directive introduces four major actions. The first action is the establishment of ‘common methodology for calculating the integrated energy performance of buildings’, which may be differentiated at the regional level. The second action is to require member states to ‘apply the new methods to minimum energy performance standards’ for new buildings. The Directive also requires that a non-residential building, when it is renovated, be brought to the level of efficiency of new buildings. This latter requirement is a very important action due to the slow turnover and renovation cycle of buildings, and considering that major renovations to inefficient older buildings may occur several times before they are finally removed from the stock. This represents a pioneer effort in energy-efficiency policy; it is one of the few policies worldwide to target existing buildings. The third action is to set up ‘certification schemes for new and existing buildings’ (both residential and non-residential), and in the case of public buildings to require the public display of energy performance certificates. These certificates are intended to address the landlord/tenant barrier, by facilitating the transfer of information on the relative energy performance of buildings and apartments. Information from the certification process must be made available for new and existing commercial buildings and for dwellings when they are constructed, sold, or rented. The last action mandates Member States to establish ‘regular inspection and assessment of boilers and heating/cooling installations’. The European Climate Change Programme (ECCP, 2001) estimated that CO2 emissions to be tapped by implementation of this directive by 2010 are 35–45 million tCO2-eq at costs below 20 EUR/tCO2-eq, which is 16–20% of the total cost-effective potential associated with buildings at these costs in 2010.
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professionals in the building industry, including plumbers and electricians, is a major impediment to the construction of low-energy buildings. In part, this reflects inadequate training at universities and technical schools, where the curricula often mirror the fragmentation seen in the building design profession. There is a significant need in most countries to create comprehensive, integrated programmes at universities and other educational establishments to train the future building professional in the design and construction of low-energy buildings. The value of such programmes is significantly enhanced if they have an outreach component to upgrade the skills and knowledge of practicing professionals – for example, by assisting in the use of computer simulation tools as part of the integrated design process. The education of end-users and raising their awareness about energy-efficiency opportunities is also important. Good explanation (e.g., user-friendly manuals) is often a condition for proper installation and functioning of energy-efficient buildings and components. Since optimal operation and regular maintenance are often as important as the technological efficiency in determining overall energy consumption of equipment, accessible information and awareness raising about these issues during and after purchase are necessary. This need for widespread education is beginning to be reflected in the curricula of some countries: Japan’s and Germany’s schools increasingly teach the importance of energy savings (ECCJ, 2006; Hamburger-bildungsserver, 2006). Better education is also relevant for professionals such as plumbers and electricians. Incentives for consumers are generally needed along with the information programs to have significant effect (Shipworth, 2000).
Occasionally with financial support from government or utility companies, these programmes may provide trained energy auditors to conduct on-site inspections of buildings, perform most of the calculations for the building owner and offer recommendations for energy-efficiency investments or operational measures, as well as other cost-saving actions (e.g., reducing peak electrical demand, fuel-switching). The implementation of the audit recommendations can be voluntary for the owner, or mandated-such as in the Czech Republic and Bulgaria, which require that installations with energy consumption above a certain limit conduct an energyefficiency audit and implement the low-cost measures (ÜrgeVorsatz et al., 2003). In India, all large commercial buildings have to conduct an energy audit at specified intervals of time (The Energy Conservation Act, 2001). The EU EPB Directive mandates audits and the display of the resulting certificate in an increasing number of situations (see Box 6.3). 6.8.2
Policies and programmes aimed at appliances, lighting and office/consumer plug loads
Appliances, equipment (including information and communication technology) and lighting systems in buildings typically have very different characteristics from those of the building shell and installed equipment, including lower investment costs, shorter lifetimes, different ownership characteristics and simpler installation and maintenance. Thus, the barriers to energy-efficient alternatives are also different to some extent, warranting a different policy approach. This section provides an overview of policies specific to appliances, lighting and plug-in equipment.
Energy audit programmes assist consumers in identifying opportunities for upgrading the energy efficiency of buildings.
Box 6.4: Global efforts to combat unneeded standby and low-power mode consumption in appliances Standby and low-power-mode (LoPoMo) electricity consumption of appliances is growing dramatically worldwide, while technologies exist that can eliminate or reduce a significant share of related emissions. The IEA (2001) estimated that standby power and LoPoMo waste may account for as much as 1% of global CO2 emissions and 2.2% of OECD electricity consumption. Lebot et al. (2000) estimated that the total standby power consumption in an average household could be reduced by 72%, which would result in emission reductions of 49 million tCO2 in the OECD. Various instruments – including minimum energy efficiency performance standards (MEPS), labelling, voluntary agreements, quality marks, incentives, tax rebates and energy-efficient procurement policies – are applied globally to reduce the standby consumption in buildings (Commission of the European Communities, 1999), but most of them capture only a small share of this potential. The international expert community has been urging a 1-Watt target (IEA, 2001). In 2002, the Australian government introduced a ‘one-watt’ plan aimed at reducing the standby power consumption of individual products to less than one watt. To reach this, the National Appliance and Equipment Energy Efficiency Committee has introduced a range of voluntary and mandatory measures to reduce standby – including voluntary labelling, product surveys, MEPS, industry agreements and mandatory labelling (Commonwealth of Australia, 2002). As of mid-2006, the only mandatory standard regarding standby losses in the world has been introduced in California (California Energy Commission, 2006), although in the USA the Energy Policy Act of 2005 directed the USDOE to evaluate and adopt low standby power standards for battery chargers.
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6.8.2.1
Standards and labelling
Energy-efficiency performance standards and labels (S&L) for appliances and lighting are increasingly proving to be effective vehicles for transforming markets and stimulating adoption of new, more efficient technologies and products. Since the 1990s, 57 countries have legislated efficiency standards and/or labels, applied to a total of 46 products as of 2004 (Wiel and McMahon, 2005). Today, S&L programmes are among the most cost-effective instruments across the economy to reduce GHG emissions, with typically large negative costs (see Table 6.6). Products subject to standards or labels cover all end-uses and fuel types, with a focus on appliances, information and communications devices, lighting, heating and cooling equipment and other energy-consuming products. Endorsement and comparison labels19 induce manufacturers to improve energy efficiency and provide the means to inform consumers of the product’s relative or absolute performance and (sometimes) energy operating costs. According to studies evaluating the effectiveness of labels (Thorne and Egan, 2002), those that show the annual energy cost savings appear to be more effective than labels that present life-cycle cost savings. An advantage of a ‘categorical’ labelling scheme, showing a number of stars or an A-B-C rating, is that it is often easiest for consumers to understand and to transfer their understanding of the categories from one product purchase to others. The categories also provide a useful framework for implementing rebates, tax incentives, or preferential public procurement programmes, while categorical labels on HVAC and other installed equipment make it easy for the building inspector to check for code compliance. A downside of a categorical labelling system can be that if standards are not revised from time to time, there is no stimulus to the manufacturers to develop more efficient appliances and the whole market will be able to deliver appliances fitting the highest efficiency class. Despite widely divergent approaches, national S&L programmes have resulted in significant cost-effective GHG savings. The US programme of national, mandatory energyefficiency standards began in 1978. By 2004, the programme had developed (and, in 17 cases, updated) standards for 39 residential and commercial products. The total federal expenditure for implementing the US appliance standards adopted so far (US$ 2 per household) is estimated to have induced US$ 1270 per household of net-present-value savings during the lifetimes of the products affected. Projected annual residential carbon reductions in 2020 due to these appliance standards amount roughly to 9% of projected US residential carbon emissions in the 2020 (base case) (Meyers et al., 2002). In addition, the US Energy Star endorsement label programme estimates savings of 13.2 million tCO2-eq and US$ 4.2 billion
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in 2004 (US EPA, 2005), and projects that the programme will save 0.7 billion tonnes of CO2 over the period 2003 to 2010, growing to 1.8 billion tonnes of CO2 over the period 2003 to 2020, if the market target penetration is reached (Webber et al., 2003). According to the IEA (2003a), GHG abatement through appliance standards and labelling in Europe by 2020 will be achieved at a cost of –65 US$/tCO2 in North America and –169 €/tCO2 (–191 US$/tCO2) (i.e., both at substantial ‘net benefit’). An evaluation of the impact of the EU appliance-labelling scheme showed a dramatic shift in the efficiency of refrigerators sold in the EU in the first decade of its S&L programme, as displayed in Figure 6.5 (Bertoldi, 2000). Japan imposes stringent energy efficiency standards on equipment through its ‘Top Runner Programme’ by distinctly setting the target values based on the most energy-efficient model on the market at the time of the value-setting process. Energy-efficiency values and a rating mark are voluntarily displayed in promotional materials so that consumers can consider energy-efficiency when purchasing (Murakoshi and Nakagami, 2005). A recent IEA report (2003a) concludes that, without existing policy measures such as energy labelling, voluntary agreements, and MEPS, electricity consumption in OECD countries in 2020 would be about 12% (393 TWh) higher than is now predicted. The report further concludes that the current policies are on course to produce cumulative net cost savings of € 137 billion (US$ 155 billion) in OECD-Europe from 1990 to 2020. As large as these benefits are, the report found that much greater benefits could be attained if existing policies were strengthened. A study of China’s energy-efficiency standards (Fridley and Lin, 2004) estimated savings from eight new MEPS and nine energy-efficiency endorsement labels. The study concluded that, during the first 10 years of implementation, these measures will save 200 TWh (equivalent to all of China’s residential electricity consumption in 2002) and 250 MtCO2. Among other countries, Korea shows similar evidence of the impact of labelling, as does the EU (CLASP, 2006). Recently, Australia transformed its S&L programme in order to aggressively improve energy efficiency (NAEEEC, 2006). In the past few years, strong regional and global S&L efforts have also emerged, offering a more coordinated pathway to promote S&L and improve the cost-effectiveness and market impact of the programmes. One of these pathways is regional harmonization. The IEA (2003b) identifies several forms of multilateral cooperation, including: ‘collaboration’ in the design of tests, labels and standards; ‘harmonization’ of the test procedures and the energy-efficiency thresholds used in labels and standards; and ‘coordination’ of programme implementation and monitoring efforts. However, while easing certain trade restrictions, harmonization of standards and testing methods
19 Endorsement labels (or “quality marks”) define a group of products as “efficient” when they meet pre-specified criteria, while comparison labels allow buyers to compare the efficiency of products based on factual information about their absolute or relative performance.
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can have the unintended consequence of overcoming cultural and other differences that affect consumer preferences, possibly leading to increased levels of energy consumption (Moezzi and Maithili, 2002; Biermayer and Lin, 2004). 6.8.2.2
Voluntary agreements
Voluntary agreements, in which the government and manufacturers agree to a mutually acceptable level of energy use per product, are being used in place of, or in conjunction with, mandatory MEPS to improve the energy efficiency of appliances and equipment. In the European context, this includes a wide range of industry actions such as industry covenants, negotiated agreements, long-term agreements, selfregulation, codes of conduct, benchmarking and monitoring schemes (Rezessy and Bertoldi, 2005). Voluntary measures can cover equipment, building design and operation and public, and private sector energy management policies and practices. Examples include Green Lights in the EU and the Energy Star programmes in the USA, as well as successful EU actions for the reduction of standby losses and efficiency improvement of washing machines and cold appliances. Industry often favours voluntary agreements to avoid the introduction of mandatory standards (Bertoldi, 1999). For the public authorities, voluntary agreements offer a faster approach than mandatory regulation and are often acceptable if they include the following three elements: (i) commitments by those manufacturers accounting for most of the equipment sold, (ii) quantified commitments to significant improvements in the energy efficiencies of the
equipment over a reasonable time scale, and (iii) an effective monitoring scheme (Commission of the European Communities, 1999). Voluntary agreements are considered especially useful in conjunction with other instruments and if mandatory measures are available as a backup or to encourage industry to deliver the targeted savings, such as for the case of cold appliances in the EU (Commission of the European Communities, 1999; JägerWaldau, 2004). 6.8.3
Cross-cutting policies and programmes that support energy efficiency and/or CO2 mitigation in buildings
This section reviews a range of policies and programmes that do not focus specifically on either buildings and installed equipment, or on appliances and smaller plug-in devices in buildings, but may support energy efficiency and emissions reductions – including effects across other end-use sectors. 6.8.3.1
Utility demand-side management programmes
One of the most successful approaches to achieving energy efficiency in buildings in the USA has been utility-run demandside management (DSM) programmes. However, there are important disincentives that need to be removed or lowered for utilities to be motivated in pursuing DSM programmes. The most important of these difficulties, (i.e., that utilities make profits from selling electricity, not from reducing sales) can be overcome by regulatory changes in which the utility will avoid 425
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revenue losses from reduced sales, and in some cases also receive profits from successful execution of DSM programmes.
6.8.3.2
The major large-scale experience with utility DSM has been in the United States primarily in the west coast and New England, but now spreading to other parts of the country. Spending on DSM was US$ 1.35 billion in 2003 (York and Kushler, 2005), and since California is more than doubling its expenditure to US$ 700 million/yr for the next three years, DSM spending in the United States will increase substantially.
Market-based energy pricing and energy taxes represent a broad measure for saving energy in buildings. The effect of energy taxes depends on energy price elasticity, that is the percent change in energy demand associated with each 1% change in price. In general, residential energy price elasticities are low in the richest countries. In the UK, long-run price elasticity for the household sector is only –0.19 (Eyre, 1998), in the Netherlands –0.25 (Jeeninga and Boots, 2001) and in Texas only –0.08 (Bernstein and Griffin, 2005). However, if energy expenditures reach a significant proportion of disposable incomes, as in many developing countries and economies in transition, elasticities – and therefore the expected impact of taxes and subsidy removal – may be higher, although literature is sparse on the subject. In Indonesia, price elasticity was –0.57 in the period from 1973 to 1990 and in Pakistan –0.33 (De Vita et al., 2006). Low elasticity means that taxes on their own have little impact; it is behavioural and structural barriers that need to be addressed (Carbon Trust, 2005). To have a significant impact on CO2 emission reduction, excise taxes have to be substantial. This is only the case in a few countries (Figure 6.6): the share of excise tax compared to total fuel price differs considerably by country.
These programmes have had a major impact. For the United States as a whole, where DSM investments have been 0.5% of revenues, savings are estimated to be 1.9% of revenues. For California, cumulative annual savings are estimated to be 7.5% of sales, while DSM investment has been less than 2% (1.2% in 2003). Overall, for each of the years 1996 through 2003, DSM has produced average annual savings of about 33.5 MtCO2-eq annually for the USA, an annual net savings of more than US$ 3.7 billion (York and Kushler, 2005). There are numerous opportunities to expand utility DSM programmes: in the United States, by having other states catch up with the leaders (especially California at present), much more so in Europe and other OECD countries, which have little experience with such programmes offered by utilities, and over time in developing countries, as well.
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Figure 6.6: Electricity and gas prices and taxes for households in 2004 Notes: Total price is listed when no breakdown available to show taxes; total taxes are provided when no breakdown on excise and VAT (GST). Country name abbreviations (according to the ISO codes except Chinese Taipei): DK – Denmark, JP – Japan, CH – Switzerland, FR – France, GB – United Kingdom, HU – Hungary, TR – Turkey, PO – Poland, NZ – New Zealand, AU - Australia, MX – Mexico, US – United States of America, KR – South Korea, CT – Chinese Taipei, CA – Canada, ZA – South Africa*, KZ – Kazakhstan, RU – Russia. * South Africa data is for 2003. Sources: IEA, 2006a; RAO, 2006.
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In stark contrast to imposing energy taxes, energy prices are subsidized in many countries. This results in under-pricing of energy, which reduces the incentive to use it more efficiently. Energy subsidies are also typically much larger, per GJ, in developing and transition countries than in most industrial economies (Markandya, 2000). The total value of energy subsidies of eight of the largest non-OECD countries (China, Russia, India, Indonesia, Iran, South Africa, Venezuela and Kazakhstan), covering almost 60% of total non-OECD energy demand, was around US$ 95 billion in 1998 (UNEP OECD/ IEA, 2002). In 1999, the IEA estimated that removing the energy subsidies in those eight countries would reduce primary energy use by 13%, lower CO2 emissions by 16% and raise GDP by almost 1%. While it may be economically and environmentally desirable, it is a socially sensitive task to remove end-user subsidies, especially in the residential sector. Since the bulk of these subsidies are found in countries with low incomes and high fuel-poverty rates, their removal can cause a substantial financial burden for families and even institutions. This, in turn, can lead to bankruptcy, increased payment arrears, energy theft and generally increased social tensions (ERRA/LGI, 2002; Ürge-Vorsatz et al., 2003), ultimately leading to disincentives to improve efficiency. Therefore, a drastic subsidy removal is often accompanied by social compensation programmes. One potentially important form of alternative compensation – although not frequently used to date – is assistance to low-income households to invest in energy-saving measures that reduce fuel costs and GHG emissions in the long term as opposed to direct cash assistance providing short-term relief (ERRA/LGI, 2002). For a number of years, the US government has provided 1.5–2.0 billion US$/yr to help low-income households pay their energy bills (LIHEAP, 2005), and smaller amounts budgeted for grants to ‘weatherize’ many of these same households with efficiency measures that help to permanently reduce monthly fuel and electricity bills (Schweitzer and Berry, 1999). Some forms of energy subsidies can have positive energy and environmental effects. For example, subsidies on oil products and electricity in developing countries reduce deforestation and also reduce indoor pollution as poor, rural households switch away from traditional energy sources, such as wood, straw, crop residues and dung. These positive effects, however, can be better achieved through other means – e.g., the introduction of safe and efficient cookers and heaters utilizing these renewable sources. The challenge is to design and reform energy subsidies so they favour the efficient and environmentally sound use of energy systems (UNEP OECD/IEA, 2002) 6.8.3.3
Investment subsidies, financial incentives and other fiscal measures
As noted in Section 6.5.5, applying an integrated design process (IDP) can result in buildings that use 35–70% less energy than conventional designs, at little or no additional capital
cost, but with a potential increase in the design cost. Providing financial incentives for the design process rather than financial incentives for the capital cost of the building is an approach used in several regions, such as by Canada in its Commercial Building Incentive Program (Larsson, 2001), by California in its Savings By Design programme and in Germany under the SolarBau programme (Reinhart et al., 2000). Going beyond IDP, other measures – particularly those that include renewable energy options – entail significant added capital costs. Many developed countries offer incentives for such measures (IEA, 2004f). Types of financial support include subsidies, tax reduction (or tax credit) schemes and preferential loans or funds, with investment subsidies being the most frequently used (IEA, 2004f). Capital subsidy programmes and tax exemption schemes for both new construction and existing buildings have been introduced in nine OECD countries out of 20 surveyed (OECD, 2003). Several countries (USA, France, Belgium, UK and the Netherlands) combine their financial incentive policy for the existing building stock with social policy to assist low-income households (IEA, 2004a; VROM, 2006; USDOE, 2006). Increasingly, eligibility requirements for financial support are tied to CO2 emission reduction (IEA, 2004a; KfW Group, 2006). Within the Energy Star Homes programme in the USA, houses that meet the energy-efficiency standard are eligible for a special mortgage (Nevin and Watson, 1998; Energystar, 2006). Financial incentives for the purchase of energy-efficient appliances are in place in some countries, including Mexico, the USA, Belgium, Japan and Greece (Boardman, 2004; IEA, 2004f). Incentives also encourage connection to district heating in Austria, Denmark and Italy. There has been limited assessment of the efficiency of these schemes. The cost-effectiveness of subsidy-type schemes can vary widely, depending on programme design. Joosen et al. (2004) have estimated that subsidy programmes for residential buildings cost Dutch society 32–105 US$/tCO2, whereas this range for the commercial sector was between 64 and 123 US$/tCO2. A variety of financial incentives available simultaneously may make the decision process difficult; simplicity of the schemes might be an asset (Barnerjee and Solomon, 2003). A combination of government financial incentives and private bank loans may be more effective than a government-subsidized loan, as may combining building rating or labelling with a loan-especially when the labelling scheme has public approval. 6.8.3.4
Public sector leadership programmes and public procurement policies
Government agencies, and ultimately taxpayers, are responsible for a wide range of energy-consuming facilities and services such as government office buildings, schools and health care facilities. The government itself is often a country’s largest consumer of energy and largest buyer of energy-using equipment. The US federal government spends over US$ 10 427
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billion/yr for energy-using equipment (Harris and Johnson, 2000). Government policies and actions can thus contribute, both directly and indirectly, to energy savings and associated GHG reductions (Van Wie McGrory et al., 2002). A recent study for several EU countries (Borg et al., 2003) found a potential for direct energy savings of 20% or more in EU government facilities and operations. According to the USDOE’s Federal Energy Management Program (FEMP), average energy intensity (site energy per square meter) in federal buildings has been reduced by about 25% since 1985, while average energy intensity in US commercial buildings has stayed roughly constant (USDOE/EERE, 2005; USDOE/FEMP, 2005).
Public procurement policies can have their greatest impact on the market when they are based on widely harmonized energyefficiency specifications that can send a strong market signal to manufacturers and suppliers (Borg et al., 2003). If US agencies at all levels of government adopt the federal efficiency criteria for their own purchases, estimated annual electricity savings in the USA would be 10.8 million tonnes CO2-eq, allowing for at least one billion US$/yr savings on public energy bills (Harris and Johnson, 2000).
Indirect beneficial impacts occur when Governments act effectively as market leaders. First, government buying power can create or expand demand for energy-efficient products and services. Second, visible government energy-saving actions can serve as an example for others. Public sector energy efficiency programmes fall into five categories (Harris et al., 2005): (i) Policies and targets (energy/cost savings; CO2 reductions); (ii) Public buildings (energy-saving retrofit and operation of existing facilities, as well as sustainability in new construction), (iii) Energy-efficient government procurement; (iv) Efficiency and renewable energy use in public infrastructure (transit, roads, water and other public services); and (v) Information, training, incentives and recognition of leadership by agencies and individuals. The following paragraphs provide selected examples.
While not a ‘policy instrument’, ESCOs have become favoured vehicles to deliver energy-efficiency improvements and are promoted by a number of policies. An ESCO is a company that offers energy services, such as energy analysis and audits, energy management, project design and implementation, maintenance and operation, monitoring and evaluation of savings, property/facility management, energy and/or equipment supply and provision of energy services (e.g., space heating, lighting). ESCOs guarantee the energy savings and/or the provision of a specified level of energy service at lower cost by taking responsibility for energy-efficiency investments or/ and improved maintenance and operation of the facility. This is typically executed legally through an arrangement called ‘energy performance contracting’ (EPC). In many cases, the ESCO’s compensation is directly tied to the energy savings achieved. ESCOs can also directly provide or arrange for project financing, or assist with financing by providing an energy (cost) savings guarantee for their projects. Finally, ESCOs often retain an ongoing operational role, provide training to on-site personnel, and take responsibility for measuring and verifying the savings over the term of the project loan.
The EU Directive on Energy Performance of Buildings discussed above and in Box 6.3, includes special requirements for public building certification. UK policy requires all new and refurbished government buildings to be rated under the British Research Establishment Environmental Assessment Method (BREEAM), which includes credits for energy efficiency and reduced CO2 emissions. New government buildings must achieve a BREEAM rating of ‘Excellent,’ while major refurbishments require a ‘Good’ rating (UK/DEFRA, 2004). In the USA, a recent law requires new federal buildings to be designed 30% better for energy performance than that required by current commercial and residential building codes (U.S. Congress, 2005). Energy-efficient government purchasing and public procurement can be powerful market tools. (Borg et al., 2003; Harris et al., 2004). Energy-efficient government procurement policies are in place in several EU countries, as well as in Japan, Korea, Mexico, China and the USA (Harris et al., 2005). In the USA, in 2005, Congress passed a law mandating that all federal agencies specify and buy efficient products that qualify for the Energy Star label, or (in cases where that label does not apply) products designated by USDOE/FEMP as being among the top 25th percentile of efficient products (US Congress, 2005). Federal purchasing policies are expected to save 1.1 million tonnes CO2-eq and US$ 224 million/yr in 2010 (Harris and Johnson, 2000). 428
6.8.3.5
Promotion of energy service companies (ESCOs) and energy performance contracting (EPC)
In 2006, the US ESCO market is considered the most advanced in the world (Goldman et al., 2005), with revenues reaching about US$ 2 billion in 2002 (Lin and Deng, 2004). Most US ESCO activity (approximately 75%) is in the public sector. The market for energy-efficiency services in Western Europe was estimated to be € 150 million/yr in 2000, while the market potential was estimated at € 5–10 billion/yr (Butson, 1998; Bertoldi and Starter, 2003). Germany and Austria are the ESCO leaders in Europe, with street-lighting projects among the most common demand-side EPC projects, and public buildings the most targeted sector (Bertoldi et al., 2005; Rezessy et al., 2005). Between 1998 and 2003, 600–700 public buildings were renovated in Austria using energy performance contracting by ESCOs. Austria is now using EPCs to renovate 50% of the total floor area of federal buildings (Leutgöb, 2003). In Germany, more than 200 EPCs have been signed since the mid-1990s, primarily for public buildings (Seefeldt, 2003). In Japan, the ESCO market is growing quickly, with a focus on the commercial and public sectors (office buildings and hospitals) (Murakoshi and Nakagami, 2003). In India and Mexico, ESCOs also have targeted at least 50% of their activity in the public and
Chapter 6
Residential and commercial buildings
commercial sectors (Vine, 2005). Most ESCOs do not target the residential sector, although exceptions exist (e.g., in Nepal and South Africa). ESCOs greatly facilitate the access of building owners and operators to technical expertise and innovative project financing. They can play a central role in improving energy efficiency without burdening public budgets and regulatory intervention to markets. However, the ESCO industry does not always develop on its own and policies and initiatives may be necessary to kick-start the market. The commitment of federal and municipal authorities to use ESCOs for their energy-efficiency projects, along with supportive policies and public-private partnerships has been crucial in countries such as Germany and Austria (Brand and Geissler, 2003). In some cases, obligations imposed on electricity companies have fostered the development of ESCO activities, as in the case of Brazil, where power utilities are required to invest 1% of their net operating revenues in energy efficiency. 6.8.3.6
Energy-efficiency obligations and tradable energyefficiency certificates
Recognising that traditional energy policy tools have not achieved the magnitude of carbon savings needed to meet climate stabilization targets, a few new innovative instruments are being introduced or planned in a number of countries. Among them are the so-called ‘white certificates’, a cap-and-trade scheme (or, in some cases, an obligation without the trading element) applied to achieve energy efficiency improvements. The basic principle is an obligation for some category of economic actors (e.g., utility companies, product manufacturers or distributors and large consumers) to meet specified energy savings or programmedelivery goals, potentially coupled with a trading system based on verified and certified savings achieved (or expected) for energy-efficiency measures (the ‘white’ certificate) (ECEEE, 2004; Oikonomou et al., 2004). Energy efficiency obligation programmes without certificate trading have been operating in the UK since 1994 and in Flanders (Belgium) since 2003; white certificate schemes with a trading element were in place in 2006 in Italy, France and New South Wales. Other European countries have announced their intention to introduce similar schemes. Capturing the desired benefit of certificate trading schemes – that is minimising the costs of meeting energy savings goals – depends on the liquidity of the market. There is a tradeoff between liquidity, crucial to minimizing the costs, and manageability and transaction costs. Where transaction costs turn out to be very high, a simple energy savings obligation for electricity and gas distributors, without the complication of trading, may be a better way to deliver the desired outcome (Bertoldi and Rezessy, 2006). Since the first white certificate schemes are just starting, it remains to be seen whether this policy instrument will deliver the expected level of savings and at what cost.
In the UK, the Energy Efficiency Commitment (EEC) requires that all large gas and electricity suppliers deliver a certain quantity of energy savings by assisting customers to take energy-efficiency actions in their homes. The delivered overall savings of the first phase, 87 TWh, largely exceeded the target of 65 TWh and the target has since been increased to 130.2 TWh (Lees, 2006). 6.8.3.7
The Kyoto Protocol’s Flexibility Mechanisms
The flexibility mechanisms of the Kyoto Protocol (KP), especially the clean development mechanism (CDM) and joint implementation (JI), could offer major benefits for buildings in developing countries and economies in transition, in terms of financing, transfer of advanced technologies and knowhow, building of local capacity and demonstration effects (Woerdman, 2000; Grubb et al., 2002). Buildings should be prime targets for project-based mechanisms due to the variety and magnitude of cost-effective potentials (see section 6.5). For instance, Trexler and Associates (Margaree Consultants, 2003) estimated that building and appliance efficiency accounts for 32% of total potential in CDM in 2010 under 0 US$/tCO2 and 20% under 20 US$/tCO2. However, evidence until 2006 shows that little of this potential is expected to be unlocked during the first commitment period (Novikova et al., 2006). After initial enthusiasm in the activities implemented jointly (AIJ) phase, where 18 out of 156 registered projects were targeted to buildings, JI and CDM experience to date suggests that this pilot phase brought disappointment in building-related projects. As of February 2006, only four CDM projects out of 149 projects registered or seeking validation were for buildings, and none of the 152 approved and submitted JI projects was due to invest in buildings (Novikova et al., 2006). While it is too early to conclude that the Kyoto Protocols’s project-based mechanisms do not work well for buildings, there are no indications that this trend will reverse. A number of barriers prevent these mechanisms from fully mobilizing their benefits for buildings (Tangen and Heggelund, 2003; ECON Analysis, 2005). Chief among these is the proportionately high transaction costs due to the relatively small size of building-related projects: although these costs are around 100 €/tCO2 (124 US$/tCO2) for building-related projects, they amount only to 0.1 €/tCO2 (0.12 US$/tCO2) for very large-scale projects (Michaelowa and Jotzo, 2005). While a few hypothetical solutions have been suggested to overcome the barriers (Novikova et al., 2006), their implementation is uncertain. Another major chance opens for buildings in former communist countries with large emission surpluses through Green Investment Schemes, or the ‘greening’ of these surplus emission units, if they are constructed to accommodate small-scale energy-efficiency investments better than CDM or JI, potentially delivering over a billion tonnes of real CO2 reductions. In summary, if the KP is here to stay, the architecture of the flexible mechanisms could be revisited to address these 429
Residential and commercial buildings
shortcomings, so that the major opportunities from buildings in developing countries and EITs do not stay unutilised. A potential criterion for appraising climate regimes – in terms of their success in leveraging lowest costs mitigation options, as well as in meeting sustainable development goals – could be their success in promoting buildings-level investments in developing countries and economies in transition, reflecting their recognized importance in minimized-cost global emission mitigation efforts. 6.8.3.8
Technology research, development, demonstration and deployment (RD&D)
Chapter 6
the envisioned necessary 32 Gt global CO2 reduction by 2050 (IEA, 2006d). 6.8.4
In the buildings sector, non-CO2 greenhouse gases (halocarbons) are used as the working fluid in most vapourcompression cooling equipment, and as a blowing agent in some insulation foams including polyurethane spray foam. Background in this report is in Section 6.4.15, which is in turn a brief summary of IPCC/TEAP (2005). 6.8.4.1
Section 6.4 attested that there is already a broad array of accessible and cost-effective technologies and know-how that can abate GHG emissions in existing and new buildings to a significant extent that have not been widely adopted yet. At the same time, several recently developed technologies, including high performance windows, active glazing, vacuum insulated panels, phase change materials to increase building thermal mass, high performance reversible heat pumps and many other technologies may be combined with integrated passive solar design and result in up to 80% reduction of building energy consumption and GHG emissions. Large-scale GHG reduction in buildings requires fast and large-scale dissemination and transfer in many countries, including efficient and continuous training of professionals in the integrated approach to design and optimized use of combinations of technologies. Integrated intelligent building control systems, building- or communitylevel renewable energy generation, heat and coldness networks, coupled to building renewable energy capture components and intelligent management of the local energy market need more research, development and demonstration, and could develop significantly in the next two decades. Between 1996 and 2003 the annual worldwide RD&D budget for energy efficiency in buildings has been approximately US$ 225–280 million/yr (IEA, 2004d). The USA has been the leading country in energy research and development for buildings for over a decade. Despite the decline in US funds by 2/3rd between 1993 and 2003, down from a peak of US$ 180 million, the USA is still responsible for half of the total global expenditures (IEA, 2004d). Substantial buildings-related energy-efficiency RD&D is also sponsored in Japan (15% of global expenditure). The overall share of energy-efficiency in total energy RD&D expenditure is low, especially compared to its envisioned role in global GHG mitigation needs. In the period from 2001 to 2005 on average only 14% of all energy RD&D expenditure in IEA countries has been designated for energy-efficiency improvement (IEA, 2006c), whereas its contribution to CO2 emission reduction needs by 2050 is 45% according to the most commonly used ‘Map’ scenario of the IEA (2006d). The share dedicated to energy efficiency improvements in buildings was only 3%, in stark contrast with their 18% projected role in
430
Policies affecting non-CO2 gases
Stationary refrigeration, air conditioning and heat pump applications
A number of countries have established legislative and voluntary regimes to control emissions and use of fluorinated gases. In Europe, a number of countries have existing policies that aim at reducing leakage or discouraging the use of refrigerants containing fluorine. Regulations in the Netherlands minimize leakage rates through improved maintenance and regular inspection. Substantial taxes for refrigerants containing fluorine are levied in Scandinavian countries, and legislation in Luxembourg requires all new large cooling systems to use natural refrigerants (Harmelink et al., 2005). Some countries such as Denmark and Austria have banned the use of HFCs in selected air conditioning and refrigeration applications. In 2006 the EU Regulation 842/2006 entered into force, which requires that all medium and large stationary air conditioning applications in the EU will use certified and trained service personnel, and assures recovery of refrigerants at the end-oflife (Harmelink et al., 2005). In the USA, it has been illegal under the Clean Air Act since 1995, to vent substitutes for CFC and HCFC refrigerants during maintenance, repair and disposal of air conditioning and refrigeration equipment (US EPA, 2006). Japan, has established a target to limit HFC, PFC and SF6 emissions. Measures to meet this target include voluntary action plans by industries, mandatory recovery systems for HFCs used as refrigerants (since April 2002) and the research and development of alternatives (UNFCCC, 2006). Australia has developed an Ozone Protection and Synthetic Greenhouse Gas Management Act. Measures include supply controls though the licensing of importers, exporters and manufacturers of fluorinated gases and pre-charged refrigeration and air conditioning equipment; end-use regulations on handling, use, recovery, sale and reporting are in place (Australian Government, 2006). Canada has established a National Action Plan for the Environmental Control of ODS and their Halocarbon Alternatives (NAP). This ensures that HFCs are only used in applications where they replace ODS and requires recovery, recycling and reclamation for CFCs, HCFCs and HFCs (Canadian Council of Ministers of the Environment, 2001).
Chapter 6
6.8.4.2
Residential and commercial buildings
Insulating foams and SF6 in sound-insulating glazing
Within the European Union, Denmark and Austria have introduced legislation to ban the use of HFC for the production of several foam types (Cheminfo, 2004). Since 2006 the EU Regulation 842/2006 on certain Fluorinated Gases limits emissions and certain uses of fluorinated gases (European Commission, 2006), banning the use of HFCs in One-Component Foam from 2008, except where required to meet national safety standards. Japan has established a target to limit HFC, PFC and SF6 emissions. Measures to meet this target include voluntary action plans by industries, improved containment during the production process, less blowing agent per product, improved productivity per product and the use of non-fluorocarbon low GWP alternatives. Australia has developed an act for industries covered by the Montreal Protocol and extended voluntary arrangements for non-Montreal Protocol industries. Measures include supply controls though the licensing of importers, exporters and manufacturers of HFCs. Although there are no international proposals to phase out the use of HFCs in foams, the high costs of HFCs have naturally contributed to the minimization of their use in formulations (often by use with co-blowing agents) and by early replacement by alternative technologies based primarily on CO2, water or hydrocarbons (e.g. pentane). There is more regulatory uncertainty at regional level and in Japan some pressure exists to stop HFC-use in the foam sector. In Europe, the recently published F-Gas regulation (European Commission, 2006) only impacts the use of HFCs in one component foam (OCF) which is used primarily for gap filling in the construction sector. However, there is a requirement to put in place provisions for recovery of blowing agent at end-of-life where such provisions are technically feasible and do not entail disproportionate cost. 6.8.5
Policy options for GHG abatement in buildings: summary and conclusion
Section 6.8 demonstrates that there is a variety of government policies, programmes, and market mechanisms in many countries for successfully reducing energy-related CO2 emissions in buildings (high agreement, medium evidence). Table 6.6 (below) reviews 20 of the most important policy tools used in buildings according to two criteria from the list of criteria suggested in Chapter 13 (of the ones for which literature was available in policy evaluations): emission reduction effectiveness and cost-effectiveness. Sixty-six ex post (with a few exceptions) policy evaluation studies were identified from over 30 countries and country groups that served as a basis for the assessment.
The first column in Table 6.6 identifies the key policy instruments grouped by four major categories using a typology synthesized from several sources including Grubb (1991); Crossley et al. (2000) and Verbruggen and Bongaerts (2003): (i) control and regulatory mechanisms, (ii) economic and marketbased instruments, (iii) financial instruments and incentives, and (iv) support and information programmes and voluntary action. The second column identifies a selection of countries where the policy instrument is applied20. Then, the effectiveness in achieving CO2 reduction and cost-effectiveness were rated qualitatively based on available literature as well as quantitatively based on one or more selected case studies. Since any instrument can perform poorly if not designed carefully, or if its implementation and enforcement are compromised, the qualitative and quantitative comparisons are based on identified best practices, in order to demonstrate what impact an instrument can achieve if applied well. Finally, the table lists special conditions for success, major strengths and limitations, and co-benefits. While the 66 studies represent the majority of such evaluations available in the public domain in 2006, this sample still leaves few studies in certain categories. Therefore, the comparative findings of this assessment should be viewed as indicative rather than conclusive. Although a general caveat of comparative policy assessments is that policies act as parts of portfolios and therefore the impact of an individual instrument is difficult to delineate from those of other tools, this concern affects the assessment to a limited extent since the literature used already completed this disaggregation before evaluating individual instruments. All the instruments reviewed can achieve significant energy and CO2 savings; however the costs per tonne of CO2 saved diverge greatly. In our sample, appliance standard, building code, labelling and tax exemption policies achieved the highest CO2 emission reductions. Appliance standards, energy efficiency obligations, demand-side management programmes, public benefit charges and mandatory labelling were among the most cost-effective policy tools in the sample, all achieving significant energy savings at negative costs. Investment subsidies (as opposed to rebates for purchases of energy efficient appliances) were revealed as the least cost-effective instrument. Tax reductions for investments in energy efficiency appeared more effective than taxation. Labelling and voluntary programmes can lead to large savings at low-costs if they are combined with other policy instruments. Finally, information programmes can also achieve significant savings and effectively accompany most other policy measures.
20 Since we made a strong effort to highlight best practices from developing countries where possible, major front-running developed countries where the instrument is applied may not be listed in each applicable row of the table.
431
432 Effectivenessb
SG, PH, DZ, EG, US, GB, CN, EU
US, EU, CN, MX, KR, JP
US, CA, AU, JP, MX, CN, CR, EU
GB, BE, FR, IT, DK, IE
US, CH, DK, NL, DE, AT
Building codes
Procurement regulations
Mandatory labelling and certification programmes
Energy efficiency obligations and quotas
Utility demandside management programmes
High
High
High
High
High
High
Energy performance contracting
DE, AT, FR, SE, FI, US, JP, HU
High
Economic and market-based instruments
EU, US, JP, AU, BR, CN
Appliance standards
Control and regulatory mechanisms
Policy instrumenta
Examples of countries
High
US: 36.7 MtCO2 in 2000.
Medium
High
GB: 1.4 MtCO2/yr.
FR, SE, US, FI: 20–40% of buildings energy saved; EU:40–55MtCO2 by 2010; US: 3.2 MtCO2/yr.
High
AU: 5 M tCO2 savings 1992–2000; DK: 3.568 MtCO2.
EU: mostly at no cost, rest at <22 $/tCO2; US: Public sector: B/C ratio 1.6, Priv. sector: 2.1
US: Average costs approx. –35 $/tCO2.
Flanders: –216 $/tCO2 for households, –60 $/tCO2 for other sector in 2003; GB: –139 $/tCO2.
AU: –30 $/tCO2 abated.
MX: $1Million in purchases saves $726,000/yr; EU: <21 $/tCO2.
NL: from –189 $/tCO2 to –5 $/tCO2 for endusers, 46–109 $/tCO2 for society.
Medium
Medium
AU: –15 $/tCO2 in 2012; US: –65 $/tCO2 in 2020; EU: –194 $/tCO2 in 2020.
High
Costeffectiveness
MX: 4 cities saved 3.3 ktCO2-eq in one year; CN: 3.6 MtCO2 expected; EU: 20–44 MtCO2 potential.
HK: 1% of total electricity saved; US: 79.6 MtCO2 in 2000; EU: 35–45 MtCO2, max 60% energy savings in new buildings.
JP: 31 M tCO2 in 2010; CN: 240 MtCO2 in 10 yrs; US: 2.5% of electricity use in 2000 = 65 MtCO2, 6.5% = 223.87 MtCO2 in 2010.
Energy or emission reductions for selected best practices
Cost of GHG emission reduction for selected best practicesc
Table 6.6: The impact and effectiveness of various policy instruments aimed to mitigate GHG emission in the buildings sector
Strength: no need for public spending or market intervention, co-benefit of improved competitiveness.
DSM programmes for commercial sector tend to be more costeffective than those for residences.
Continuous improvements necessary: new energy efficiency measures, short-term incentives to transform markets etc.
Effectiveness can be boosted by combination with other instrument and regular updates.
Success factors: enabling legislation, energy efficiency labelling & testing, ambitious energy efficiency specifications.
No incentive to improve beyond target. Only effective if enforced.
Factors for success: periodical update of standards, independent control, information, communication and education.
Special conditions for success, major strengths and limitations, co-benefits
ECCP, 2003; OPET network, 2004; Singer, 2002; IEA, 2003a; World Energy Council, 2004; Goldman et al., 2005.
IEA, 2005; Kushler et al., 2004.
UK government, 2006; Sorell, 2003; Lees, 2006; Collys, 2005; Bertoldi & Rezessy, 2006; Defra, 2006.
World Energy Council, 2001; OPET network, 2004; Holt & Harrington, 2003.
Borg et al., 2003; Harris et al., 2005; Van Wie McGrory et al., 2006.
World Energy Council, 2001; Lee & Yik, 2004; Schaefer et al., 2000; Joosen et al., 2004; Geller et al., 2006; ECCP, 2001.
IEA, 2005; Schlomann et al. 2001; Gillingham et al., 2004; ECS, 2002; World Energy Council, 2004; Australian Greenhouse Office, 2005; IEA 2003a; Fridley and Lin, 2004.
References
Residential and commercial buildings Chapter 6
Low
CN, TH, CEE (JI & AIJ)
Kyoto Protocol flexible mechanismsd
BE, DK, Medium/ FR, NL, low US states
JP, SI, NL, High DE, CH, US, HK, GB
Public benefit charges
Capital subsidies, grants, subsidized loans
Voluntary certification and labelling
DE, CH, US, TH, BR, FR
SI: up to 24% energy savings for buildings, GB: 3.3 MtCO2; US:29.1 Mio BTU/yr gas savings.
Low
high in reported cases
High
US: 88 MtCO2 in 2006.
US: 0.1–0.8% of total electricity sales saved /yr, average of 0.4%.
Low
DE: household consumption reduced by 0.9%.
Low
Medium
IT: 3.64 Mt CO2 eq by 2009 expected.
CEE: 220 K tCO2 in 2000.
High
Varies, German telecom company: up to 60% energy savings for specific units.
Costeffectiveness
High Medium/ high BR: 169.6 ktCO2 in 1998, US: 13.2 MtCO2 in 2004, 2.1 bio tCO2-eq in total by 2010; TH: 192 tCO2.
Support, information and voluntary action
High
US, FR, NL, KO
Tax exemptions / reductions
Low
NO, DE, GB, NL, DK, CH
Taxation (on CO2 or household fuels)
Financial instruments and incentives
Medium
IT, FR
Energy efficiency certificate schemes
High
DE, IT, GB, SE, AT, IE, JP, PO, SK, CH
Examples Energy or emission of reductions for selected best countries Effectivenessb practices
Co-operative procurement
Policy instrumenta
Table 6.6. Continued.
BR: US$ 20 million saved.
NL: 41–105 US$/ tCO2 for soc; GB:29 US$/tCO2 for soc, –66 $/tCO2 for enduser.
From –53 US$/ tCO2 to –17 $/tCO2.
Overall B/C ratio – Commercial buildings: 5.4 – New homes: 1.6.
63 $/tCO2.
n.a.
0: Energyefficient purchasing relies on funds that would have been spent anyway.
Cost of GHG emission reduction for selected best practicesc Oak Ridge National Laboratory, 2001; Le Fur 2002; Borg et al., 2003.
References
ECS, 2005; Novikova. et al., 2006.
Effective with financial incentives, voluntary agreements and regulations.
Positive for low-income households, risk of free-riders, may induce pioneering investments.
If properly structured, stimulate introduction of highly efficient equipment and new buildings.
OPET network, 2004; Word Energy Council, 2001; Geller et al., 2006; Egan et al., 2000; Webber et al., 2003.
ECS, 2001; Martin et al., 1998; Schaefer et al., 2000; Geller et al., 2006; Berry & Schweitzer, 2003; Joosen et al., 2004; Shorrock, 2001.
Western Regional Air Partnership, 2000; Kushler et al., 2004.
Quinlan et al., 2001; Geller & Attali, 2005.
Effect depends on price World Energy Council, 2001; elasticity. Revenues can Kohlhaas, 2005. be earmarked for further efficiency. More effective when combined with other tools.
So far limited number of CDM & JI projects in buildings.
No long-term experience OPET network, 2004; Bertoldi & yet. Transaction costs Rezessy, 2006; Lees, 2006; Defra, can be high. Monitoring 2006. and verification crucial. Benefits for employment.
Success condition: energy efficiency needs to be prioritized in purchasing decisions.
Special conditions for success, major strengths and limitations, co-benefits
Chapter 6 Residential and commercial buildings
433
434
NZ, MX, PH, AR, BR, EC
DK, US, GB, CA, BR, JP
US, FR, NZ, EG, AU, CZ
ON, IT, SE, FI, JP, NO, CL
Public leadership programmes
Awareness raising, education / information campaigns
Mandatory audit & energy management requirement
Detailed billing and disclosure programmes
Medium
High, but variable
Low/ Medium
High
Medium/ High
Up to 20% energy savings.
US: Weatherization Program: 22% saved in weatherized households.
GB: Energy Efficiency Advice Centres: 10.4 K tCO2 annually.
De: 25% public sector CO2 reduction over 15 years.
US: 88 MtCO2-eq/yr UK: 15.8 MtCO2
Energy or emission reductions for selected best practices
Medium
Medium
High
High
Medium
Costeffectiveness
n.a.
US Weatherization Program: BCratio: 2.4.
BR: –66 US$/ tCO2; GB: 8 US$/ tCO2 (for all programmes of Energy Trust).
US DOE/FEMP estimates 4 US$ savings for every 1 US$ of public funds invested.
GB: 54.5–104 US$/tCO2 (Climate Change Agreements).
Cost of GHG emission reduction for selected best practicesc
Success conditions: combination with other measures and periodic evaluation. Comparability with other households is positive.
Most effective if combined with other measures such as financial incentives
More applicable in residential sector than commercial.
Can be used to demonstrate new technologies and practices. Mandatory programmes have higher potential than voluntary ones.
Can be effective when regulations are difficult to enforce. Effective if combined with financial incentives and threat of regulation.
Special conditions for success, major strengths and limitations, co-benefits
Crossley et al., 2000; Darby 2000; Roberts & Baker, 2003; Energywatch, 2005.
World Energy Council, 2001
Bender et al., 2004; Dias et al., 2004; Darby, 2006; IEA, 2005; Lutzenhiser, 1993; Ueno et al. 2006; Energy Saving Trust, 2005.
Borg et al., 2003; Harris et al., 2005; Van Wie McGrory et al., 2006; OPET, 2004.
Geller et al., 2006; Cottrell, 2004.
References
Notes: Country name abbreviations (according to the ISO codes except California, Ontario, Central and Eastern Europe and European Union): DZ – Algeria, AR – Argentina, AU – Australia, AT – Austria, BE – Belgium, BR – Brazil, CL – California, CA – Canada, CEE – Central and Eastern Europe, CN – China, CR – Costa Rica, CZ – Czech Republic, DE – Germany, Denmark – DK, EC – Ecuador, EG – Egypt, EU – European Union, FI – Finland, FR – France, GB – United Kingdom, HK – Hong Kong, HU – Hungary, IN – India, IE – Ireland, IT – Italy, JP – Japan, KR – Korea (South), MX – Mexico, NL – Netherlands, NO – Norway, ON – Ontario, NZ – New Zealand, NG – Nigeria, PH – Philippines, PO – Poland, SG – Singapore, SK – Slovakia, SI – Slovenia, CH – Switzerland, SE – Sweden, TH – Thailand, US – United States. a) For definitions of the instruments see: Crossley et al. (1999), Crossley et al. (2000), EFA (2002), Vine et al. (2003) and Wuppertal Institute (2002). b) Effectiveness of CO2 emission reduction: includes ease of implementation; feasibility and simplicity of enforcement; applicability in many locations; and other factors contributing to overall magnitude of realized savings. c) Cost-effectiveness is related to specific societal cost per unit of carbon emissions avoided. Energy savings were recalculated into emission savings using the following references for the emission factors: Davis (2003), UNEP (2000), Center for Clean Air Policy (2001). The country-specific energy price was subtracted from the cost of saved energy in order to account for the financial benefits of energy savings (Koomey and Krause, 1989), if they were not considered originally. d) Kyoto flexible mechanisms: Joint Implementation (JI), Clean Development Mechanism (CDM), International Emissions Trading (includes the Green Investment Schemes).
Mainly Western Europe, JP, US
Voluntary and negotiated agreements
Policy instrumenta
Table 6.6. Continued.
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The effectiveness of economic instruments, information programmes and regulation can be substantially enhanced if these are appropriately combined into policy packages that take advantage of synergistic effects (Ott et al., 2005). A typical example is the co-ordination of energy audit programmes with economic instruments, such as energy taxes and capital subsidy schemes. In addition, ESCOs can flourish when public procurement legislation accommodates EPCs and includes ambitious energy-efficiency or renewable energy provisions, or in the presence of an energy-saving obligation. Section 6.8 demonstrates that, during the last decades, many new policies have been initiated. However, so far only incremental progress has been achieved by these policies. In most developed countries, the energy consumption in buildings is still increasing (IEA, 2004f). Although some of this growth is offset by increased efficiency of major energy-consuming appliances, overall consumption continues to increase due to the growing demand for amenities, such as new electric appliances and increased comfort. The limited overall impact of policies so far is due to several factors: (i) slow implementation processes (e.g., as of 2006, not all European countries are on time with the implementation of the EU Buildings Directive); (ii) the lack of regular updating of building codes (requirements of many policies are often close to common practices, despite the fact that CO2-neutral construction without major financial sacrifices is already possible) and appliance standards and labelling; and (iii) insufficient enforcement. In addition, Section 6.7 demonstrated that barriers in the building sector are numerous; diverse by region, sector and end-user group, and are especially strong. There is no single policy instrument that can capture the entire potential for GHG mitigation. Due to the especially strong and diverse barriers in the residential and commercial sectors, overcoming these is only possible through a diverse portfolio of policy instruments for effective and far-reaching GHG abatement and for taking advantage of synergistic effects. Since climate change literacy, awareness of technological, cultural and behavioural choices and their impacts on emissions are important preconditions to fully operating policies, these policy approaches need to go hand in hand with programmes that increase consumer access to information, awareness and knowledge (high agreement, medium evidence). In summary, significant CO2 and other GHG savings can be achieved in buildings, often at net benefit to society (in addition to avoided climate change) and also meeting many other sustainable development and economic objectives, but this requires a stronger political commitment and more ambitious policy-making than today, including careful design of policies as well as enforcement and regular monitoring.
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6.9 Interactions of mitigation options with vulnerability, adaptation and sustainable development 6.9.1
Interactions of mitigation options with vulnerability and adaptation
In formulating climate change strategies, mitigation efforts need to be balanced with those aimed at adaptation. There are interactions between vulnerability, adaptation and mitigation in buildings through climatic conditions and energy systems. As a result of a warming climate, heating energy consumption will decline, but energy demand for cooling will increase while at the same time passive cooling techniques will become less effective. The net impact of these changes on GHG emissions is related to the available choice of primary energy used and the efficiency of technologies that are used for heating and cooling needs. Mansur et al. (2005) find that the combination of climate warming and fuel switching in US buildings from fuels to electricity results in increases in the overall energy demand, especially electricity. Other studies indicate that in European countries with moderate climate the increase in electricity for additional cooling is higher than the decrease for heating demand in winter (Levermore et al., 2004; Aebischer et al., 2006; Mirasgedis et al., 2006). Aebischer et al. (2006) finds that in Europe there is likely to be a net increase in power demand in all but the most northerly countries, and in the south a significant increase in summer peak demand is expected. Depending on the generation mix in particular countries, the net effect on carbon dioxide emissions may be an increase even where overall demand for final energy declines. Since in many countries electricity generation is largely based on fossil fuels, the resulting net difference between heating reduction and cooling increases may significantly increase the total amount of GHG emissions. This causes a positive feedback loop: more mechanical cooling emits more GHGs, thereby exacerbating warming, although the effect maybe moderate. Vulnerability of energy demand to climate is country- and region-specific. For instance, a temperature increase of 2°C is associated with an 11.6% increase in residential per capita electricity use in Florida, but with a 7.2% decrease in Washington DC (Sailor, 2001). Increased net energy demand translates into increased welfare losses. Mansur et al. (2005) found that, for a 5°C increase in temperature by 2100, the annual welfare loss in increased energy expenditures is predicted to reach US$ 40 billion for US households. Fortunately, there are many potential synergies where investments in the buildings sector may reduce the overall cost of climate change-in terms of both mitigation and adaptation. For instance, if new buildings are constructed, the design can address both mitigation and adaptation aspects. Among the most important of these are reduced cooling loads. For instance, using advanced insulation techniques and passive solar design 435
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to reduce the expected increase in air conditioning load. In addition, if high-efficiency electric appliances are used, the savings are increased due to reduced electricity demand for air conditioning, especially in commercial buildings. Roof retrofits can incorporate increased insulation and storm security in one investment. In addition, the integrated design of wellinsulated, air-tight buildings, with efficient air management and energy systems, leads not only to lower GHG emissions, but also to reduced thermal stress to occupants, reducing extreme weather-related mortality and other health effects. Furthermore, adaptive comfort, where occupants accept higher indoor (comfort) temperatures when the outside temperature is high, is now incorporated in design considerations, especially for predominantly naturally ventilated buildings (see Box 6.5).
address the core needs of such countries – these are economic growth, poverty alleviation and employment creation (OECD, 2001). Often a tension exists between the main agenda of most of these countries (poverty alleviation through increased access to energy) and climate change concerns. Increased access to modern energy for the mostly rural population has been a priority in recent years. Most countries, therefore, place more policy emphasis on increasing the supply of petroleum and electricity than on renewables or energy efficiency (Karakezi and Ranja, 2002). The success of climate change mitigation policies depends largely on the positive management of these tensions. GHG reduction strategies in developing countries have a higher chance of success if they are ‘embedded’ in poverty eradication efforts, rather than executed independently.
Policies that actively promote integrated building solutions for both mitigating and adapting to climate change are especially important for the buildings sector. It has been observed that building users responding to a warmer climate generally choose options that increase cooling energy consumption rather than other means, such as insulation, shading, or ventilation, which consume less energy. A prime example of this is the tendency of occupants of existing, poorly performing buildings (mainly in developing countries) to buy portable air conditioning units. These trends – which clearly will accelerate in warmer summers to come – may result in a significant increase of GHG emissions from the sector, enhancing the positive feedback process. However, well-designed policies supporting less energyintensive cooling alternatives can help combat these trends (see Box 6.5 and Section 6.4.4.1). Good urban planning, including increasing green areas as well as cool roofs in cities, has proven to be an efficient way to limit the heat island effect, which also aggravates the increased cooling needs (Sailor, 2002).
Fortunately, buildings offer perhaps the largest portfolio of options where such synergies can be identified. Matrices in Chapter 12 demonstrate that the impact of mitigation options in the building sector on sustainable development, for both industrialized countries and developing countries, is reported to be positive for all of the criteria used. Both Sections 6.6 above and Box 6.1 discuss many of the opportunities for positive synergies in detail; the next paragraph revisits a few of them.
6.9.2
Synergies with sustainability in developing countries
The failure of numerous development strategies in the least developed countries, most of them in Africa, to yield the expected results has been attributed to the fact that the strategies failed to
The dual challenges of climate change and sustainable development were strongly emphasised in the 2002 Millennium Development Goals (MDGs). GHG mitigation strategies are more realizable if they work mutually with MDGs towards the realization of these set objectives. For example, MDG goal seven is to ensure sustainable development, in part by reducing the proportion of people using solid fuels which will lead to the reduction of indoor air pollution (see sections 6.6.1). GHG mitigation and public health are co-benefactors in the achievement of this goal. Similarly, increased energy efficiency in buildings, or considering energy efficiency as the guiding principle during the construction of new homes, will result in both reduced energy bills – enhancing the affordability of increased energy services – and GHG abatement. If technologies that utilise locally available renewable resources in an efficient and clean way are used broadly, this provides access to ‘free’
Box 6.5: Mitigation and adaptation case study: Japanese dress codes In 2005, the Ministry of the Environment (MOE) in Japan widely encouraged businesses and the public to set air conditioning thermostats in offices to around 28°C during summer. As a part of the campaign, MOE has been promoting summer business styles (‘Cool Biz’) to encourage business people to wear cool and comfortable clothes, allowing them to work efficiently in these warmer offices. In 2005, a survey of 562 respondents by the MOE (Murakami et al., 2006) showed that 96% of the respondents were aware of ‘Cool Biz’ and 33% answered that their offices set the thermostat higher than in previous years. Based on this result, CO2 emissions were reduced by approximately 460,000 tonnes in 2005, which is equivalent to the amount of CO2 emitted from about one million Japanese households for one month. MOE will continue to encourage offices to set air conditioning in offices at 28°C and will continue to promote ‘Cool Biz.’
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energy to impoverished communities for many years and contributes to meeting other MDGs. However, for the poorest people in both developing countries and industrialised countries, the main barrier to energy-efficiency and renewable energy investments is the availability of financing for the investments. Devoting international aid or other public and private funds aimed at sustainable development to energy efficiency and renewable energy initiatives in buildings can achieve a multitude of development objectives and result in a long-lasting impact. These investments need not necessarily be executed through public subsidies, but may increasingly be achieved through innovative financing schemes, such as ESCOs or public-private partnerships. These schemes offer win-win opportunities, and leverage and strengthen markets (Blair et al., 2005). With a few exceptions, energy policies and practices in residential and commercial buildings in sub-Saharan Africa (SSA) do not take efficiency into consideration. However, energy efficiency in buildings has recently been recognised as one of the ways of increasing energy security and benefiting the environment, through energy savings (Winkler et al., 2002). South Africa, for example, has drafted an energy-efficiency strategy to promote efficiency in buildings (DME, 2004). Such policies can be promoted in other SSA countries by linking energy efficiency in buildings directly to the countries’ development agendas, by demonstrating how energy efficiency practises contribute to energy security. The positive impacts of these practices, including GHG mitigation, could then be considered as co-benefits.
6.10
Critical gaps in knowledge
During the review of the global literature, a few important areas have been identified which are not adequately researched or documented. First, there is a critical lack of literature and data about GHG emissions and mitigation options in developing countries. Whereas the situation is somewhat better in developed regions, in the vast majority of countries detailed end-use data is poorly collected or reported publicly, making analyses and policy recommendations insufficiently robust. Furthermore, there is a severe lack of robust, comprehensive, detailed and upto-date bottom-up assessments of GHG reduction opportunities and associated costs in buildings worldwide, preferably using a harmonized methodology for analysis. In existing assessments of mitigation options, co-benefits are typically not included, and in general, there is an important need to quantify and monetize these so that they can be integrated into policy decision frameworks. Moreover, there is a critical lack of understanding, characterisation and taxonomization of non-technological options to reduce GHG emissions. These are rarely included in global GHG mitigation assessment models, potentially largely underestimating overall potentials. However, our policy leverage to realise these options is also poorly understood.
Finally, literature on energy price elasticities in the residential and commercial sectors in the different regions is very limited, while essential for the design of any policies influencing energy tariffs, including GHG taxes and subsidy removal.
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7 Industry Coordinating Lead Authors: Lenny Bernstein (USA), Joyashree Roy (India)
Lead Authors: K. Casey Delhotal (USA), Jochen Harnisch (Germany), Ryuji Matsuhashi (Japan), Lynn Price (USA), Kanako Tanaka (Japan), Ernst Worrell (The Netherlands), Francis Yamba (Zambia), Zhou Fengqi (China)
Contributing Authors: Stephane de la Rue du Can (France), Dolf Gielen (The Netherlands), Suzanne Joosen (The Netherlands), Manaswita Konar (India), Anna Matysek (Australia), Reid Miner (USA), Teruo Okazaki (Japan), Johan Sanders (The Netherlands), Claudia Sheinbaum Parado (Mexico)
Review Editors: Olav Hohmeyer (Germany), Shigetaka Seki (Japan)
This chapter should be cited as: Bernstein, L., J. Roy, K. C. Delhotal, J. Harnisch, R. Matsuhashi, L. Price, K. Tanaka, E. Worrell, F. Yamba, Z. Fengqi, 2007: Industry. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Industry
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Table of Contents Executive Summary ................................................ 449
7.6
Barriers to industrial GHG mitigation .... 475
7.1
7.7
Sustainable Development (SD) implications of industrial GHG mitigation ..................... 477
7.8
Interaction of mitigation technologies with vulnerability and adaptation ...................... 478
7.9
Effectiveness of and experience with policies .............................................................. 478
Introduction ................................................... 451
7.1.1
Status of the sector ......................................... 451
7.1.2
Development trends ........................................ 451
7.1.3
Emission trends .............................................. 452
7.2
Industrial mitigation matrix ....................... 454
7.3
Industrial sector-wide operating procedures and technologies ............................................. 456
7.3.1
Management practices, including benchmarking ................................................. 456
7.3.2
Energy efficiency ............................................. 457
7.3.3
Fuel switching, including the use of waste materials ........................................................ 458
7.3.4 Heat and power recovery................................. 458 7.3.5
Renewable energy ........................................... 459
7.3.6
Materials efficiency and recycling .................... 459
7.3.7
Carbon dioxide Capture and Storage (CCS), including oxy-fuel combustion ........................ 460
Kyoto mechanisms (CDM and JI) ..................... 478
7.9.2
Voluntary GHG programmes and agreements... 479
7.9.3
Financial instruments: taxes, subsidies and access to capital ............................................. 481
7.9.4
Regional and national GHG emissions trading programmes.................................................... 482
7.9.5
Regulation of non-CO2 gases .......................... 482
7.9.6
Energy and technology policies ....................... 482
7.9.7
Sustainable Development policies.................... 483
7.9.8
Air quality policies ........................................... 483
7.9.9
Waste management policies ........................... 483
Process-specific technologies and measures .......................................................... 460
7.10 Co-benefits of industrial GHG mitigation......................................................... 484
7.4.1
Iron and steel .................................................. 460
7.4.2
Non-ferrous metals .......................................... 463
7.11 Technology Research, Development, Deployment and Diffusion (RDD&D) ...... 485
7.4.3
Chemicals and fertilizers .................................. 464
7.11.1 Public sector ................................................... 486
7.4.4
Petroleum refining ........................................... 466
7.11.2 Private sector .................................................. 487
7.4.5
Minerals .......................................................... 467
7.4.6
Pulp and paper................................................ 469
7.4.7
Food ............................................................... 470
7.4.8
Other industries ............................................... 471
7.4.9
Inter-industry options....................................... 472
7.12.2 System transitions, inertia and decision-making .............................................. 487
Short- and medium-term mitigation potential and cost ........................................... 472
7.13 Key uncertainties and gaps in knowledge ........................................................ 487
7.4
7.5
7.5.1
Electricity savings............................................ 473
7.5.2 Non-CO2 gases ............................................... 473 7.5.3
448
7.9.1
Summary and comparison with other studies ... 473
7.12 Long-term outlook, system transitions, decision-making and inertia ....................... 487 7.12.1 Longer-term mitigation options ........................ 487
References .................................................................. 488
Chapter 7
Industry
EXECUTIVE SUMMARY Industrial sector emissions of greenhouse gases (GHGs) include carbon dioxide (CO2) from energy use, from nonenergy uses of fossil fuels and from non-fossil fuel sources (e.g., cement manufacture); as well as non-CO2 gases. • Energy-related CO2 emissions (including emissions from electricity use) from the industrial sector grew from 6.0 GtCO2 (1.6 GtC) in 1971 to 9.9 GtCO2 (2.7 GtC) in 2004. Direct CO2 emissions totalled 5.1 Gt (1.4 GtC), the balance being indirect emissions associated with the generation of electricity and other energy carriers. However, since energy use in other sectors grew faster, the industrial sector’s share of global primary energy use declined from 40% in 1971 to 37% in 2004. In 2004, developed nations accounted for 35%; transition economies 11%; and developing nations 53% of industrial sector energy-related CO2 emissions. • CO2 emissions from non-energy uses of fossil fuels and from non-fossil fuel sources were estimated at 1.7 Gt (0.46 GtC) in 2000. • Non-CO2 GHGs include: HFC-23 from HCFC-22 manufacture, PFCs from aluminium smelting and semiconductor processing, SF6 from use in electrical switchgear and magnesium processing and CH4 and N2O from the chemical and food industries. Total emissions from these sources (excluding the food industry, due to lack of data) decreased from 470 MtCO2-eq (130 MtC-eq) in 1990 to 430 MtCO2-eq (120 MtC-eq) in 2000. Direct GHG emissions from the industrial sector are currently about 7.2 GtCO2-eq (2.0 GtC-eq), and total emissions, including indirect emissions, are about 12 GtCO2-eq (3.3 GtC-eq) (high agreement, much evidence). Approximately 85% of the industrial sector’s energy use in 2004 was in the energy-intensive industries: iron and steel, nonferrous metals, chemicals and fertilizers, petroleum refining, minerals (cement, lime, glass and ceramics) and pulp and paper. In 2003, developing countries accounted for 42% of iron and steel production, 57% of nitrogen fertilizer production, 78% of cement manufacture and about 50% of primary aluminium production. Many industrial facilities in developing nations are new and include the latest technology with the lowest specific energy use. However, many older, inefficient facilities remain in both industrialized and developing countries. In developing countries, there continues to be a huge demand for technology transfer to upgrade industrial facilities to improve energy efficiency and reduce emissions (high agreement, much evidence).
1
Many options exist for mitigating GHG emissions from the industrial sector (high agreement, much evidence). These options can be divided into three categories: • Sector-wide options, for example more efficient electric motors and motor-driven systems; high efficiency boilers and process heaters; fuel switching, including the use of waste materials; and recycling. • Process-specific options, for example the use of the bioenergy contained in food and pulp and paper industry wastes, turbines to recover the energy contained in pressurized blast furnace gas, and control strategies to minimize PFC emissions from aluminium manufacture. • Operating procedures, for example control of steam and compressed air leaks, reduction of air leaks into furnaces, optimum use of insulation, and optimization of equipment size to ensure high capacity utilization. Mitigation potential and cost in 2030 have been estimated through an industry-by-industry assessment for energy-intensive industries and an overall assessment for other industries. The approach yielded mitigation potentials at a cost of <100 US$/ tCO2-eq (<370 US$/tC-eq) of 2.0 to 5.1 GtCO2-eq/yr (0.6 to 1.4 GtC-eq/yr) under the B2 scenario1. The largest mitigation potentials are located in the steel, cement, and pulp and paper industries and in the control of non-CO2 gases. Much of the potential is available at <50 US$/tCO2-eq (<180 US$/tC-eq). Application of carbon capture and storage (CCS) technology offers a large additional potential, albeit at higher cost (medium agreement, medium evidence). Key uncertainties in the projection of mitigation potential and cost in 2030 are the rate of technology development and diffusion, the cost of future technology, future energy and carbon prices, the level of industry activity in 2030, and climate and non-climate policy drivers. Key gaps in knowledge are the base case energy intensity for specific industries, especially in economies-in-transition, and consumer preferences. Full use of available mitigation options is not being made in either industrialized or developing nations. In many areas of the world, GHG mitigation is not demanded by either the market or government regulations. In these areas, companies will invest in GHG mitigation if other factors provide a return on their investment. This return can be economic, for example energy efficiency projects that provide an economic payout, or it can be in terms of achieving larger corporate goals, for example a commitment to sustainable development. The slow rate of capital stock turnover is also a barrier in many industries, as is the lack of the financial and technical resources needed to implement mitigation options, and limitations in the ability of
A1B and B2 refer to scenarios described in the IPCC Special Report on Emission Scenarios (IPCC, 2000b). The A1 family of scenarios describe a future with very rapid econoic growth, low population growth, and rapid introduction of new and more efficient technologies. B2 describes a world ‘in which emphasis is on local solutions to economic, social, and environmental sustainability’. It features moderate population growth, intermediate levels of economic development, and less rapid and more diverse technological change than the A1B scenario.
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industrial firms to access and absorb technological information about available options (high agreement, much evidence). Industry GHG investment decisions, many of which have long-term consequences, will continue to be driven by consumer preferences, costs, competitiveness and government regulation. A policy environment that encourages the implementation of existing and new mitigation technologies could lead to lower GHG emissions. Policy portfolios that reduce the barriers to the adoption of cost-effective, low-GHG-emission technology can be effective (medium agreement, medium evidence). Achieving sustainable development will require the implementation of cleaner production processes without compromising employment potential. Large companies have greater resources, and usually more incentives, to factor environmental and social considerations into their operations than small and medium enterprises (SMEs), but SMEs provide the bulk of employment and manufacturing capacity in many developing countries. Integrating SME development strategy into the broader national strategies for development is consistent with sustainable development objectives (high agreement, much evidence). Industry is vulnerable to the impacts of climate change, particularly to the impacts of extreme weather. Companies can adapt to these potential impacts by designing facilities that are resistant to projected changes in weather and climate, relocating plants to less vulnerable locations, and diversifying raw material sources, especially agricultural or forestry inputs. Industry is also vulnerable to the impacts of changes in consumer preference and government regulation in response to the threat of climate change. Companies can respond to these by mitigating their own emissions and developing lower-emission products (high agreement, much evidence).
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While existing technologies can significantly reduce industrial GHG emissions, new and lower-cost technologies will be needed to meet long-term mitigation objectives. Examples of new technologies include: development of an inert electrode to eliminate process emissions from aluminium manufacture; use of carbon capture and storage in the ammonia, cement and steel industries; and use of hydrogen to reduce iron and non-ferrous metal ores (medium agreement, medium evidence). Both the public and the private sectors have important roles in the development of low-GHG-emission technologies that will be needed to meet long-term mitigation objectives. Governments are often more willing than companies to fund the higher risk, earlier stages of the R&D process, while companies should assume the risks associated with actual commercialisation. The Kyoto Protocol’s Clean Development Mechanism (CDM) and Joint Implementation (JI), and a variety of bilateral and multilateral programmes, have the deployment, transfer and diffusion of mitigation technology as one of their goals (high agreement, much evidence). Voluntary agreements between industry and government to reduce energy use and GHG emissions have been used since the early 1990s. Well-designed agreements, which set realistic targets, include sufficient government support, often as part of a larger environmental policy package, and include a real threat of increased government regulation or energy/GHG taxes if targets are not achieved, can provide more than business-asusual energy savings or emission reductions. Some voluntary actions by industry, which involve commitments by individual companies or groups of companies, have achieved substantial emission reductions. Both voluntary agreements and actions also serve to change attitudes, increase awareness, lower barriers to innovation and technology adoption, and facilitate co-operation with stakeholders (medium agreement, much evidence).
Chapter 7
7.1 Introduction This chapter addresses past, ongoing, and short (to 2010) and medium-term (to 2030) future actions that can be taken to mitigate GHG emissions from the manufacturing and process industries.2 Globally, and in most countries, CO2 accounts for more than 90% of CO2-eq GHG emissions from the industrial sector (Price et al., 2006; US EPA, 2006b). These CO2 emissions arise from three sources: (1) the use of fossil fuels for energy, either directly by industry for heat and power generation or indirectly in the generation of purchased electricity and steam; (2) nonenergy uses of fossil fuels in chemical processing and metal smelting; and (3) non-fossil fuel sources, for example cement and lime manufacture. Industrial processes also emit other GHGs, e.g.: • Nitrous oxide (N2O) is emitted as a byproduct of adipic acid, nitric acid and caprolactam production; • HFC-23 is emitted as a byproduct of HCFC-22 production, a refrigerant, and also used in fluoroplastics manufacture; • Perfluorocarbons (PFCs) are emitted as byproducts of aluminium smelting and in semiconductor manufacture; • Sulphur hexafluoride (SF6) is emitted in the manufacture, use and, decommissioning of gas insulated electrical switchgear, during the production of flat screen panels and semiconductors, from magnesium die casting and other industrial applications; • Methane (CH4) is emitted as a byproduct of some chemical processes; and • CH4 and N2O can be emitted by food industry waste streams. Many GHG emission mitigation options have been developed for the industrial sector. They fall into three categories: operating procedures, sector-wide technologies and processspecific technologies. A sampling of these options is discussed in Sections 7.2–7.4. The short- and medium-term potential for and cost of all classes of options are discussed in Section 7.5, barriers to the application of these options are addressed in Section 7.6 and the implication of industrial mitigation for sustainable development is discussed in Section 7.7. Section 7.8 discusses the sector’s vulnerability to climate change and options for adaptation. A number of policies have been designed either to encourage voluntary GHG emission reductions from the industrial sector or to mandate such reductions. Section 7.9 describes these policies and the experience gained to date. Co-benefits of reducing GHG emissions from the industrial sector are discussed in Section 7.10. Development of new technology is key to the cost-
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effective control of industrial GHG emissions. Section 7.11 discusses research, development, deployment and diffusion in the industrial sector and Section 7.12, the long-term (post-2030) technologies for GHG emissions reduction from the industrial sector. Section 7.13 summarizes gaps in knowledge. 7.1.1
Status of the sector
This chapter focuses on the mitigation of GHGs from energy-intensive industries: iron and steel, non-ferrous metals, chemicals (including fertilisers), petroleum refining, minerals (cement, lime, glass and ceramics) and pulp and paper, which account for most of the sector’s energy consumption in most countries (Dasgupta and Roy, 2000; IEA, 2003a,b; Sinton and Fridley, 2000). The food processing industry is also important because it represents a large share of industrial energy consumption in many non-industrialized countries. Each of these industries is discussed in detail in Section 7.4. Globally, large enterprises dominate these industries. However, small- and medium-sized enterprises (SMEs) are important in developing nations. For example, in India, SMEs have significant shares in the metals, chemicals, food and pulp and paper industries (GOI, 2005). There are 39.8 million SMEs in China, accounting for 99% of the country’s enterprises, 50% of asset value, 60% of turnover, 60% of exports and 75% of employment (APEC, 2002). While regulations are moving large industrial enterprises towards the use of environmentally sound technology, SMEs may not have the economic or technical capacity to install the necessary control equipment (Chaudhuri and Gupta, 2003; Gupta, 2002) or are slower to innovate (Swamidass, 2003). These SME limitations create special challenges for efforts to mitigate GHG emissions. However, innovative R&D for SMEs is also taking place for this sector (See Section 7.7). 7.1.2
Development trends
The production of energy-intensive industrial goods has grown dramatically and is expected to continue growing as population and per capita income increase. Since 1970, global annual production of cement increased 271%; aluminium, 223%; steel, 84% (USGS, 2005), ammonia, 200% (IFA, 2005) and paper, 180% (FAO, 2006). Much of the world’s energy-intensive industry is now located in developing nations. China is the world’s largest producer of steel (IISI, 2005), aluminium and cement (USGS, 2005). In 2003, developing countries accounted for 42% of global steel production (IISI, 2005), 57% of global nitrogen fertilizer production (IFA, 2004), 78% of global cement manufacture and about 50% of global primary aluminium production (USGS,
For the purposes of this chapter, industry includes the food processing and paper and pulp industries, but the growing of food crops and trees is covered in Chapters 8 and 9 respectively. The production of biofuels is covered in Chapter 4. This chapter also discusses energy conversions, such as combined heat and power and coke ovens, and waste management that take place within industrial plants. These activities also take place in dedicated facilities, which are discussed in Chapters 4 and 10 respectively.
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Table 7.1: Industrial sector final energy, primary energy and energy-related carbon dioxide emissions, nine world regions, 1971–2004 Final energy (EJ) 1971
Energy-related carbon dioxide, including indirect emissions from electricity use (MtCO2)
Primary energy (EJ)
1990
2004
1971
1990
2004
1971
1990
2004
Pacific OECD
6.02
8.04
10.31
8.29
11.47
14.63
524
710
853
North America
20.21
19.15
22.66
25.88
26.04
28.87
1,512
1,472
1512
Western Europe
14.78
14.88
16.60
19.57
20.06
21.52
1,380
1,187
1126
3.75
4.52
2.81
5.46
7.04
3.89
424
529
263
11.23
18.59
9.87
15.67
24.63
13.89
1,095
1,631
856
Developing Asia
7.34
19.88
34.51
9.38
26.61
54.22
714
2,012
4098
Latin America
2.79
5.94
8.22
3.58
7.53
10.87
178
327
469
Sub-Saharan Africa
1.24
2.11
2.49
1.70
2.98
3.60
98
178
209
Middle East/North Africa
0.83
4.01
6.78
1.08
4.89
8.63
65
277
470
68.18
97.13
114.25
90.61
131.25
160.13
5,990
8,324
9855
Central and Eastern Europe EECCA
World
Notes: EECCA = countries of Eastern Europe, the Caucasus and Central Asia. Biomass energy included. Industrial sector ‘final energy’ use excludes energy consumed in refineries and other energy conversion operations, power plants, coal transformation plants, etc. However, this energy is included in ‘primary energy’. Upstream energy consumption was reallocated by weighting electricity, petroleum and coal products consumption with primary factors reflecting energy use and loses in energy industries. Final energy includes feedstock energy consumed, for example in the chemical industry. ‘CO2 emissions’ in this table are higher than in IEA’s Manufacturing Industries and Construction category because they include upstream CO2 emissions allocated to the consumption of secondary energy products, such as electricity and petroleum fuels. To reallocate upstream CO2 emissions to final energy consumption, we calculate CO2 emission factors, which are multiplied by the sector’s use of secondary energy. Source: Price et al., 2006.
2005). Since many facilities in developing nations are new, they sometimes incorporate the latest technology and have the lowest specific emission rates (BEE, 2006; IEA, 2006c). This has been demonstrated in the aluminium (Navarro et al., 2003), cement (BEE, 2003), fertilizer (Swaminathan and Sukalac, 2004) and steel industries (Tata Steel, Ltd., 2005). However, due to the continuing need to upgrade existing facilities, there is a huge demand for technology transfer (hardware, software and knowhow) to developing nations to achieve energy efficiency and emissions reduction in their industrial sectors (high agreement, much evidence). New rules introduced both domestically and through the multilateral trade system, foreign buyers, insurance companies, and banks require SMEs to comply with higher technical (e.g., technical barriers to trade), environmental (ISO, 1996), and labour standards (ENDS-Directory, 2006). These efforts can be in conflict with pressures for economic growth and increased employment, for example in China, where the government’s efforts to ban the use of small-scale coke-producing facilities for energy efficiency and environmental reasons have been unsuccessful due to the high demand for this product (IEA, 2006a).
3
Competition within the developing world for export markets, foreign investment, and resources is intensifying. Multinational enterprises seeking out new markets and investments offer both large enterprises (Rock, 2005) and capable SMEs the opportunity to insert themselves into global value chains through subcontracting linkages, while at the same time increasing competitive pressure on other enterprises, which could lose their existing markets. Against this backdrop, SMEs, SME associations, support institutions, and governments in transition and developing countries face the challenge of adopting new approaches and fostering SME competitiveness. Integration of SME development strategy in the broader national strategies for technology development, sustainable development and/ or poverty reduction and growth is under consideration in transition and developing countries (GOI, 2004). 7.1.3
Emission trends
Total industrial sector GHG emissions are currently estimated to be about 12 GtCO2-eq/yr (3.3 GtC-eq/yr) (high agreement, much evidence). Global and sectoral data on final energy use, primary energy use3, and energy-related CO2 emissions including indirect emissions related to electricity use, for 1971 to 2004 (Price et al., 2006), are shown in Table 7.1. In
Primary energy associated with electricity and heat consumption was calculated by multiplying the amount of elec-tricity and heat consumed by each end-use sector by eletricity and heat primary factors. Primary factors were derived as the ratio of fuel inputs at power plants to electricity or heat delivered. Fuel inputs for electricity production were separated from inputs to heat production, with fuel inputs in combined heat and power plants being separated into fuel inputs for electricity and heat production according to the shares of electricity and heat produced in these plants. In order to calculate primary energy for non-fossil fuel (hydro, nuclear, renewables), we followed the direct equivalent method (SRES method): the primary energy of the non-fossil fuel energy is accounted for at the level of secondary energy, that is, the first usable energy form or “currency” available to the energy system (IPCC, 2000b).
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Table 7.2: Projected industrial sector final energy, primary energy and energy-related CO2 emissions, based on SRES Scenarios, 2010–2030. A1B Scenario
Final energy (EJ)
Pacific OECD
Energy-related carbon dioxide, including indirect emissions from electricity use (MtCO2)
Primary energy (EJ)
2010
2020
2030
2010
2020
2030
2010
2020
2030
10.04
10.68
11.63
14.19
14.25
14.52
1,170
1,169
1,137
North America
24.95
26.81
28.34
32.32
32.84
32.94
1,875
1,782
1,650
Western Europe
16.84
18.68
20.10
24.76
25.45
25.47
1,273
1,226
1,158
Central and Eastern Europe
6.86
7.74
8.57
9.28
10.28
10.99
589
608
594
EECCA
20.82
24.12
27.74
28.83
32.20
35.43
1,764
1,848
1,853
Developing Asia
39.49
54.00
72.50
62.09
84.64
109.33
4,827
6,231
7,340
Latin America
18.20
26.58
33.13
29.14
38.72
51.09
1,492
2,045
2,417
7.01
10.45
13.70
13.27
19.04
27.40
833
1,286
1,534
Sub-Saharan Africa Middle East/North Africa World
14.54
22.21
29.17
20.34
29.20
39.32
1,342
1,888
2,224
158.75
201.27
244.89
234.32
286.63
346.48
15,165
18,081
19,908
B2 Scenario
Final energy (EJ) 2010
2020
Energy-related carbon dioxide including indirect emissions from electricity use (MtCO2)
Primary energy (EJ) 2030
2010
2020
2030
2010
2020
2030
Pacific OECD
10.83
11.64
11.38
14.27
14.17
12.83
980
836
688
North America
20.23
20.82
21.81
28.64
29.28
29.18
1,916
1,899
1,725
Western Europe
14.98
14.66
14.35
19.72
18.56
17.69
1,270
1,154
1,063
3.42
4.30
5.03
4.44
5.28
6.06
327
380
424
EECCA
12.65
14.74
16.96
16.06
19.06
22.33
1,093
1,146
1,208
Developing Asia
40.68
53.62
67.63
55.29
72.42
90.54
4,115
4,960
5,785
Latin America
11.46
15.08
18.24
15.78
20.10
24.84
950
1,146
1,254
Sub-Saharan Africa
2.75
4.96
10.02
4.33
7.53
14.51
260
345
665
Middle East/North Africa
8.12
9.67
12.48
13.90
15.51
19.22
791
888
1,080
125.13
149.49
177.90
172.44
201.92
237.19
11,703
12,755
13,892
Central and Eastern Europe
World
Note: Biomass energy included, EECCA = countries of Eastern Europe, the Caucasus and Central Asia. Source: Price et al. (2006).
1971, the industrial sector used 91 EJ of primary energy, 40% of the global total of 227 EJ. By 2004, industry’s share of global primary energy use declined to 37%. The developing nations’ share of industrial CO2 emissions from energy use grew from 18% in 1971 to 53% in 2004. In 2004, energy use by the industrial sector resulted in emissions of 9.9 GtCO2 (2.7 GtC), 37% of global CO2 emissions from energy use. Direct CO2 emissions totalled 5.1 Gt (1.4 GtC), the balance being indirect emissions associated with the generation of electricity and other energy carriers. In 2000, CO2 emissions from non-energy uses of fossil fuels (e.g., production of petrochemicals) and from non-fossil fuel sources (e.g., cement
manufacture) were estimated to be 1.7 GtCO2 (0.46 GtC) (Olivier and Peters, 2005). As shown in Table 7.3, industrial emissions of non-CO2 gases totalled about 0.4 GtCO2-eq (0.1 GtC-eq) in 2000 and are projected to be at about the same level in 2010. Direct GHG emissions from the industrial sector are currently about 7.2 GtCO2-eq (2.0 GtC-eq), and total emissions, including indirect emissions, are about 12 GtCO2-eq (3.3 GtCeq). Table 7.2 shows the results for the industrial sector of the disaggregation of two of the emission scenarios (see footnote 1), A1B and B2, produced for the IPCC Special Report on Emissions Scenarios (SRES) (IPCC, 2000b) into four subsectors 453
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Table 7.3: Projected industrial sector emissions of non-CO2 GHGs, MtCO2-eq/yr Region
1990
2000
2010
2030
Pacific OECD
38
53
47
49
North America
147
117
96
147
Western Europe
159
96
92
109
Central and Eastern Europe
31
21
22
27
EECCA
37
20
21
26
Developing Asia
34
91
118
230
Latin America
17
18
21
38
6
10
11
21
Sub-Saharan Africa Middle East/North Africa World
2
3
10
20
470
428
438
668
Notes: Emissions from refrigeration equipment used in industrial processes included; emissions from all other refrigeration and air conditioning applications excluded. EECCA = countries of Eastern Europe, the Caucasus and Central Asia. Source: US EPA, 2006b.
Table 7.4: Projected baseline industrial sector emissions of non-CO2 GHGs Emissions (MtCO2-eq/yr)
Industrial sector 1990
2000
2010
223
154
164
190
0
52
93
198
HFC-23 emissions from HCFC-22 production
77
96
45
106
SF6 emission from use of electrical equipment (excluding manufacture)
42
27
46
74
PFC emission from aluminium production
98
58
39
51
9
23
35
20
12
9
4
9
N2O emissions from adipic/nitric acid production HFC/PFC emissions from substitutes for ozone-depleting substancesa
PFC and SF6 emissions from semiconductor manufacture SF6 emissions from magnesium production N2O emission from caprolactam manufacture Total a
2030
8
10
13
20
470
428
438
668
Emissions from refrigeration equipment used in industrial processes included; emissions from all other refrigeration and air conditioning applications excluded.
Source: US EPA, 2006a,b.
and nine world regions (Price et al., 2006). These projections show energy-related industrial CO2 emissions of 14 and 20 GtCO2 in 2030 for the B2 and A1B scenarios, respectively. In both scenarios, CO2 emissions from industrial energy use are expected to grow significantly in the developing countries, while remaining essentially constant in the A1 scenario and declining in the B2 scenario for the industrialized countries and countries with economies-in-transition.
GHG emissions decreased from 1990 to 2000, and there are many programmes underway to further reduce these emissions (See Sections 7.4.2 and 7.4.8.). Therefore Table 7.3 shows the US EPA’s ‘technology adoption’ scenario, which assumes continued compliance with voluntary industrial targets. Table 7.4 shows these emissions by industrial process.4
7.2 Industrial mitigation matrix Table 7.3 shows projections of non-CO2 GHG emissions from the industrial sector to 2030 extrapolated from data to 2020 (US EPA 2006a,b). US EPA provides the only comprehensive data set with baselines and mitigation costs over this time frame for all gases and all sectors. However, baselines differ substantially for sectors covered by other studies, for example IPCC/TEAP (2005). As a result of mitigation actions, non-CO2
4
A wide range of technologies have the potential for reducing industrial GHG emissions (high agreement, much evidence). They can be grouped into categories, for example energy efficiency, fuel switching and power recovery. Within each category, some technologies, such as the use of more efficient
Tables 7.3 and 7.4 include HFC emissions from refrigeration equipment used in industrial processes and food storage, but not HFC emissions from other refrigeration and air conditioning applications. The tables also do not include HFCs from foams or non-CO2 emissions from the food industry. Foams should be considered in the buildings sector. Global emissions from the food industry are not available, but are believed to be small compared with the totals presented in these tables.
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Benchmarking; Energy management systems; Efficient motor systems, boilers, furnaces, lighting and HVAC; Process integration
Smelt reduction, Near net shape casting, Scrap preheating, Dry coke quenching
Inert anodes, Efficient cell designs
Membrane separations, Reactive distillation
Membrane separation Refinery gas
Precalciner kiln, Roller mill, fluidized bed kiln
Cullet preheating Oxyfuel furnace
Efficient pulping, Efficient drying, Shoe press, Condebelt drying
Efficient drying, Membranes
Sector
Sector wide
Iron & Steel
Non-Ferrous Metals
Chemicals
Petroleum Refining
Cement
Glass
Pulp and Paper
Food
Biogas, Natural gas
Biomass, Landfill gas
Natural gas
Waste fuels, Biogas, Biomass
Natural gas
Biomass fuels (bark, black liquor)
Black liquor gasification combined cycle
Biomass, Biogas, Solar drying
n.a.
Air bottoming cycle
Anaerobic digestion, Gasification
Biomass fuels, Biogas
Biofuels
Charcoal
Biomass, Biogas, PV, Wind turbines, Hydropower
Renewables
Drying with gas turbine, power recovery
Pressure recovery turbine, hydrogen recovery
Pre-coupled gas turbine, Pressure recovery turbine, H2 recovery
Top-gas pressure recovery, Byproduct gas combined cycle
Natural gas, oil or plastic injection into the BF
Natural gas
Cogeneration
Power recovery
Coal to natural gas and oil
Fuel switching
Recycling, Non-wood fibres
Increased cullet use
Slags, pozzolanes
Bio-feedstock
Recycled plastics, biofeedstock
Scrap
Scrap
Recycled inputs
Feedstock change
Fibre orientation, Thinner paper
High-strength thin containers
Blended cement Geo-polymers
Linear low density polyethylene, highperformance Plastics
High strength steel
Product change
Reduction process losses, Closed water use
Reduction cutting and process losses
Re-usable containers
Increased efficiency transport sector
Recycling, Thinner film and coating, Reduced process losses
Recycling, thinner film and coating
Recycling, High strength steel, Reduction process losses
Material efficiency
Table 7.5: Selected examples of industrial technology for reducing greenhouse-gas emissions (not comprehensive). Technologies in italics are under demonstration or development
n.a.
n.a.
n.a.
Control technology for N2O/CH4
N2O, PFCs, CFCs and HFCs control
PFC/SF6 controls
n.a.
Non-CO2 GHG
O2 combustion in lime kiln
O2 combustion
O2 combustion in kiln
From hydrogen production
Application to ammonia, ethylene oxide processes
Hydrogen reduction, Oxygen use in blast furnaces
Oxy-fuel combustion, CO2 separation from flue gas
CO2 sequestration
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electric motors and motor systems, are broadly applicable across all industries; while others, such as top-gas pressure recovery in blast furnaces, are process-specific. Table 7.5 presents selected examples of both classes of technologies for a number of industries. The table is not comprehensive and does not cover all industries or GHG mitigation technologies.
7.3 Industrial sector-wide operating procedures and technologies This section discusses sector-wide mitigation options. Barriers to the implementation of these options are discussed in Section 7.6. 7.3.1
Management practices, including benchmarking
Management tools are available to reduce GHG emissions, often without capital investment or increased operating costs. Staff training in both skills and the company’s general approach to energy efficiency for use in their day-to-day practices has been shown to be beneficial (Caffal, 1995). Programmes, for example reward systems that provide regular feedback on staff behaviour, have had good results. Even when energy is a significant cost for an industry, opportunities for improvement may be missed because of organizational barriers. Energy audit and management programmes create a foundation for improvement and provide guidance for managing energy throughout an organization. Several countries have instituted voluntary corporate energy management standards, for example Canada (Natural Resources Canada, n.d.), Denmark (Gudbjerg, 2005) and the USA (ANSI, 2005). Others, for example India, through the Bureau of Energy Efficiency (GOI 2004, 2005), promote energy audits. Integration of energy management systems into broader industrial management systems, allowing energy use to be managed for continuous improvement in the same manner as labour, waste and other inputs are managed, is highly beneficial (McKane et al., 2005). Documentation of existing practices and planned improvements is essential to achieving a transition from energy efficiency programmes and projects dependent on individuals to processes and practices that are part of the corporate culture. Software tools are available to help identify energy saving opportunities (US DOE, n.d.-a; US EPA, n.d.). Energy Audits and Management Systems. Companies of all sizes use energy audits to identify opportunities for reducing energy use, which in turn reduces GHG emissions. For example, in 2000, Exxon Mobil implemented its Global Energy Management System with the goal of achieving a 15% reduction in energy use in its refineries and chemical plants (Eidt, 2004). Okazaki et al. (2004) estimate that approximately 10% of total energy consumption in steel making could be 456
saved through improved energy and materials management. Mozorov and Nikiforov (2002) reported an even larger 21.6% efficiency improvement in a Russian iron and steel facility. For SMEs in Germany, Schleich (2004) reported that energy audits help overcome several barriers to energy efficiency, including missing information about energy consumption patterns and energy saving measures. Schleich also found that energy audits conducted by engineering firms were more effective than those conducted by utilities or trade associations. GHG Inventory and Reporting Systems. Understanding the sources and magnitudes of its GHG emissions gives industry the capability to develop business strategies to adapt to changing government and consumer requirements. Protocols for inventory development and reporting have been developed; the Greenhouse Gas Protocol developed by the World Resources Institute and World Business Council for Sustainable Development (WRI/WBCSD, 2004) is the most broadly used. The Protocol defines an accounting and reporting standard that companies can use to ensure that their measurements are accurate and complete. Several industries (e.g., aluminium, cement, chemical and pulp and paper) have developed specific calculation tools to implement the Protocol. Other calculation tools have been developed to estimate GHG emissions from office-based business operations and to quantify the uncertainty in GHG measurement and estimation (WRI/WBCSD, 2005). Within the European Union, GHG reporting guidelines have been developed for companies participating in the EU Emission Trading System. GHG Management Systems. Environmental quality management systems such as ISO 14001 (ISO, 1996), are being used by many companies to build capacity for GHG emission reduction. For example, the US petroleum industry developed their own standard based on systems developed by various companies (API, 2005). The GHG emissions reduction opportunities identified by these management systems are evaluated using normal business criteria, and those meeting the current business or regulatory requirements are adopted. Those not adopted represent additional capacity that could be used if business, government, or consumer requirements change. Benchmarking. Companies can use benchmarking to compare their operations with those of others, to industry average, or to best practice, to determine whether they have opportunities to improve energy efficiency or reduce GHG emissions. Benchmarking is widely used in industry, but benchmarking programmes must be carefully designed to comply with laws ensuring fair competition, and companies must develop their own procedures for using the information generated through these programmes. The petroleum industry has the longest experience with energy efficiency benchmarking through the use of an industry-accepted index developed by a private company (Barats, 2005). Many benchmarking programmes are developed through trade associations or ad hoc consortia of companies, and their details are often proprietary. However, ten Canadian potash
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operations published the details of their benchmarking exercise (CFI, 2003), which showed that increased employee awareness and training was the most frequently identified opportunity for improved energy performance. The success of the aluminium industry’s programmes is discussed in Section 7.4.2. Several governments have supported the development of benchmarking programmes in various forms, for example Canada, Flanders (Belgium), the Netherlands, Norway and the USA. As part of its energy and climate policy the Dutch government has reached an agreement with its energyintensive industry that is explicitly based on industry’s energy efficiency performance relative to that of comparable industries worldwide. Industry is required to achieve world best practice in terms of energy efficiency. In return, the government refrains from implementing additional climate policies. By 2002 this programme involved companies using 94% of the energy consumed by industry in the Netherlands. Phylipsen et al. (2002) critiqued the agreement, and conclude that it would avoid emissions of 4 to 9 MtCO2 (1.1 to 2.5 MtC) in 2012 compared to a business-as-usual scenario, but that these emission reductions were smaller than those that would be achieved by a continuation of the Long-Term Agreements with industry (which ended in 2000) that called for a 2%/yr improvement in energy efficiency. The Flemish covenant, agreed in 2002, uses a similar approach. As of 1 January 2005, 177 companies had joined the covenant, which projects cumulative emissions saving of 2.45 MtCO2 (0.67 MtC) in 2012 (Government of Flanders, 2005). In the USA, EPA’s Energy STAR for Industry programme has developed a benchmarking system for selected industries, for example automotive assembly plants, cement and wet corn milling (Boyd, 2005). The system is used by programme participants to evaluate the performance of their individual plants against a distribution of the energy performance of US peers. Other benchmarking programmes compare individual facilities to world best practice (Galitsky et al., 2004). 7.3.2
Energy efficiency
IEA (2006a) reports ‘The energy intensity of most industrial processes is at least 50% higher than the theoretical minimum determined by the laws of thermodynamics. Many processes have very low energy efficiency and average energy use is much higher than the best available technology would permit.’ This provides a significant opportunity for reducing energy use and its associated CO2 emissions. The major factors affecting energy efficiency of industrial plants are: choice and optimization of technology, operating procedures and maintenance, and capacity utilization, that is the fraction of maximum capacity at which the process is operating. Many studies (US DOE, 2004; IGEN/BEE; n.d.) have shown that large amounts of energy can be saved and CO2 emissions avoided by strict adherence to carefully designed operating and maintenance procedures. Steam and compressed
air leaks, poorly maintained insulation, air leaks into boilers and furnaces and similar problems all contribute to excess energy use. Quantification of the amount of CO2 emission that could be avoided is difficult, because, while it is well known that these problems exist, the information on their extent is case-specific. Low capacity utilization is associated with more frequent shutdowns and poorer thermal integration, both of which lower energy efficiency and raise CO2 emissions. In view of the low energy efficiency of industries in many developing counties, in particular Africa (UNIDO, 2001), application of industry-wide technologies and measures can yield technical and economic benefits, while at the same time enhance environmental integrity. Application of housekeeping and general maintenance on older, less-efficient plants can yield energy savings of 10–20%. Low-cost/minor capital measures (combustion efficiency optimisation, recovery and use of exhaust gases, use of correctly sized, high efficiency electric motors and insulation, etc.) show energy savings of 20–30%. Higher capital expenditure measures (automatic combustion control, improved design features for optimisation of piping sizing, and air intake sizing, and use of variable speed drive motors, automatic load control systems and process residuals) can result in energy savings of 40–50% (UNIDO, 2001, BakayaKyahurwa, 2004). Electric motor driven systems provide a large potential for improvement of industry-wide energy efficiency. De Keulenaer et al., (2004) report that motor-driven systems account for approximately 65% of the electricity consumed by EU-25 industry. Xenergy (1998) gave similar figures for the USA, where motor-driven systems account for 63% of industrial electricity use. The efficiency of motor-driven systems can be increased by improving the efficiency of the electric motor through reducing losses in the motor windings, using better magnetic steel, improving the aerodynamics of the motor and improving manufacturing tolerances. However, the motor is only one part of the system, and maximizing efficiency requires properly sizing of all components, improving the efficiency of the end-use devices (pumps, fans, etc.), reducing electrical and mechanical transmission losses, and the use of proper operation and maintenance procedures. Implementing high-efficiency motor driven systems, or improving existing ones, in the EU-25 could save about 30% of the energy consumption, up to 202 TWh/yr, and avoid emissions of up to 100 MtCO2/yr (27.2 MtC/yr) (De Keulenaer et al., 2004). In the USA, use of more efficient electric motor systems could save over 100 TWh/yr by 2010, and avoid emissions of 90 MtCO2/yr (24.5 MtC/yr) (Xenergy, 1998). A study of the use of variable speed drives in selected African food processing plants, petroleum refineries, and municipal utility companies with a total motor capacity of 70,000 kW resulted in a potential saving of 100 ktCO2-eq/yr (27 ktC/yr), or between 30–40%, at an internal rate of return of 40% (CEEEZ, 2003). IEA (2006b) estimates the global potential to be >20–25%, but a number of barriers have limited the optimization of motor systems (See Section 7.6). 457
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Typical estimates indicate that about 20% of compressed air is lost through leakage. US DOE has developed best practices to identify and eliminate sources of leakage (US DOE, n.d.-a). IEA (2006a) estimates that steam generation consumes about 15% of global final industrial energy use. The efficiency of current steam boilers can be as high as 85%, while research in the USA aims to develop boilers with an efficiency of 94%. However, in practice, average efficiencies are often much lower. Efficiency measures exist for both boilers and distribution systems. Besides general maintenance, these include improved insulation, combustion controls and leak repair in the boiler, improved steam traps and condensate recovery. Studies in the USA identified energy-efficiency opportunities with economically attractive potentials up to 18–20% (Einstein et al., 2001; US DOE, 2002). Boiler systems can also be upgraded to cogeneration systems. Efficient high-pressure boilers using process residuals like bagasse are now available (Cornland et al., 2001) and can be used to replace traditional boilers (15–25 bar) in the sugar industry. The high-pressure steam is used to generate electricity for own use with a surplus available for export to the grid (see also 7.3.4). For example, a boiler with a 60 MW steam turbine system in a 400 t/hour sugar factory could provide a potential surplus of 40 MW of zero-carbon electricity, saving 400 ktCO2/ yr (Yamba and Matsika, 2003). Similar technology installed at an Indian sugar mill increased the crushing period from 150 to 180 days, and exported an average of 10 MW of zero carbon electricity to the grid (Sobhanbabu, 2003).
CO2 emissions by 10–20%. These values are still applicable. A variety of industries are using methane from landfills as a boiler fuel (US EPA, 2005). Waste materials (tyres, plastics, used oils and solvents and sewerage sludge) are being used by a number of industries. Even though many of these materials are derived from fossil fuels, they can reduce CO2 emissions compared to an alternative in which they were landfilled or burned without energy recovery. The steel industry has developed technology to use wastes such as plastics (Ziebek and Stanek, 2001) as alternative fuel and feedstock’s. Pretreated plastic wastes have been recycled in coke ovens and blast furnaces (Okuwaki, 2004), reducing CO2 emissions by reducing both emissions from incineration and the demand for fossil fuels. In Japan, use of plastics wastes in steel has resulted in a net emissions reduction of 0.6 MtCO2eq/yr (Okazaki et al., 2004). Incineration of wastes (e.g., tyres, municipal and hazardous waste) in cement kilns is one of the most efficient methods of disposing of these materials (Cordi and Lombardi, 2004; Houillon and Jolliet, 2005). Heidelberg Cement (2006) reported using 78% waste materials (tyres, animal meal and grease, and sewerage sludge) as fuel for one of its cement kilns. The cement industry, particularly in Japan, is investing to allow the use of municipal waste as fuel (Morimoto et al., 2006). Cement companies in India are using non-fossil fuels, including agricultural wastes, sewage, domestic refuse and used tyres, as well as wide range of waste solvents and other organic liquids; coupled with improved burners and burning systems (Jain, 2005).
Furnaces and process heaters, many of which are tailored for specific applications, can be further optimized to reduce energy use and emissions. Efficiency improvements are found in most new furnaces (Berntsson et al., 1997). Research is underway to further optimize combustion processes by improving furnace and burner designs, preheating combustion air, optimizing combustion controls (Martin et al., 2000); and using oxygen enrichment or oxy-fuel burners (See Section 7.3.7). These techniques are already being applied in specific applications.
Humphreys and Mahasenan (2002) estimated that global CO2 emissions could be reduced by 12% through increased use of waste fuels. However, IEA (2006a) notes that use of waste materials is limited by their availability, Also, use of these materials for fuel must address their variable composition, and comply with all applicable environmental regulations, including control of airborne toxic materials.
7.3.3
Energy recovery provides major energy efficiency and mitigation opportunities in virtual all industries. Energy recovery techniques are old, but large potentials still exist (Bergmeier, 2003). Energy recovery can take different forms: heat, power and fuel recovery. Fuel recovery options are discussed in the specific industry sectors in Section 7.4. While water (steam) is the most used energy recovery medium, the use of chemical heat sinks in heat pumps, organic Rankine cycles and chemical recuperative gas turbines, allow heat recovery at lower temperatures. Energy-efficient process designs are often based on increased internal energy recovery, making it hard to define the technology or determine the mitigation potential.
Fuel switching, including the use of waste materials
While some industrial processes require specific fuels (e.g., metallurgical coke for iron ore reduction)5, many industries use fuel for steam generation and/or process heat, with the choice of fuel being determined by cost, fuel availability and environmental regulations. The TAR (IPCC, 2001a) limited its consideration of industrial fuel switching to switches within fossil fuels (replacing coal with oil or natural gas), and concluded, based on a comparison of average and lowest carbon intensities for eight industries, that such switches could reduce
5
Options for fuel switching in those processes are discussed in Section 7.4.
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7.3.4
Heat and power recovery
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Heat is used and generated at specific temperatures and pressures and discarded afterwards. The discarded heat can be re-used in other processes onsite, or used to preheat incoming water and combustion air. New, more efficient heat exchangers or more robust (e.g., low-corrosion) heat exchangers are being developed continuously, improving the profitability of enhanced heat recovery. In industrial sites the use of low-temperature waste heat is often limited, except for preheating boiler feed water. Using heat pumps allows recovery of the low-temperature heat for the production of higher temperature steam. While there is a significant potential for heat recovery in most industrial facilities, it is important to design heat recovery systems that are energy-efficient and cost-effective (i.e., process integration). Even in new designs, process integration can identify additional opportunities for energy efficiency improvement. Typically, cost-effective energy savings of 5 to 40% are found in process integration analyses in almost all industries (Martin et al., 2000; IEA-IETS, n.d.). The wide variation makes it hard to estimate the overall potential for energy-efficiency improvement and GHG mitigation. However, Martin et al. (2000) estimated the potential fuel savings from process integration in US industry to be 10% above the gain for conventional heat recovery systems. Einstein et al. (2001) and the US DOE (2002) estimated an energy savings potential of 5 to 10% above conventional heat recovery techniques. Power can be recovered from processes operating at elevated pressures using even small pressure differences to produce electricity through pressure recovery turbines. Examples of pressure recovery opportunities are blast furnaces, fluid catalytic crackers and natural gas grids (at sites where pressure is reduced before distribution and use). Power recovery may also include the use of pressure recovery turbines instead of pressure relief valves in steam networks and organic Rankine cycles from lowtemperature waste streams. Bailey and Worrell (2005) found a potential savings of 1 to 2% of all power produced in the USA, which would mitigate 21 MtCO2 (5.7 MtC). Cogeneration (also called Combined Heat and Power, CHP) involves using energy losses in power production to generate heat for industrial processes and district heating, providing significantly higher system efficiencies. Cogeneration technology is discussed in Section 4.3.5. Industrial cogeneration is an important part of power generation in Germany and the Netherlands, and is the majority of installed cogeneration capacity in many countries. Laurin et al. (2004) estimated that currently installed cogeneration capacity in Canada provided a net emission reduction of almost 30 MtCO2/yr (8.18 MtC/yr). Cogeneration is also well established in the paper, sugar and chemical industries in India, but not in the cement industry due to lack of indigenously proven technology suitable for high dust loads. The Indian government is recommending adoption of technology already in use in China, Japan and Southeast Asian countries (Raina, 2002).
Industry
There is still a large potential for cogeneration. Mitigation potential for industrial cogeneration is estimated at almost 150 MtCO2 (40 MtC) for the USA (Lemar, 2001), and 334 MtCO2 (91.1 MtC) for Europe (De Beer et al., 2001). Studies also have been performed for specific countries, for example Brazil (Szklo et al., 2004), although the CO2 emissions mitigation impact is not always specified. 7.3.5
Renewable energy
The use of biomass is well established in some industries. The pulp and paper industry uses biomass for much of its energy needs (See Section 7.4.6.). In many developing countries the sugar industry uses bagasse and the edible oils industry uses byproduct wastes to generate steam and/or electricity (See Section 7.4.7.). The use of bagasse for energy is likely to grow as more becomes available as a byproduct of sugar-based ethanol production (Kaltner et al., 2005). When economically attractive, other industries use biomass fuels, for example charcoal in blast furnaces in Brazil (Kim and Worrell, 2002a). These applications will reduce CO2 emissions, but will only achieve zero net CO2 emissions if the biomass is grown sustainably. Industry also can use solar or wind generated electricity, if it is available. The potential for this technology is discussed in Section 4.3.3. The food and jute industries make use of solar energy for drying in appropriate climates (Das and Roy, 1994). The African Rural Energy Enterprise Development initiative is promoting the use of solar food driers in Mali and Tanzania to preserve fresh produce for local use and for the commercial market (AREED, 2000). Concentrating solar power could be used to provide process heat for industrial purposes, though there are currently no commercial applications (IEA-SolarPACES, n.d.). 7.3.6
Materials efficiency and recycling
Materials efficiency refers to the reduction of energy use by the appropriate choice of materials and recycling. Many of these options are applicable to the transport and building sectors and are discussed in Chapter 5, section 5.3.1 and Chapter 6, section 6.4. Recycling is the best-documented material efficiency option for the industrial sector. Recycling of steel in electric arc furnaces accounts about a third of world production and typically uses 60–70% less energy (De Beer et al., 1998). This technology, and options for further energy savings, are discussed in Section 7.4.1. Recycling aluminium requires only 5% of the energy of primary aluminium production. Recycled aluminium from used products and sources outside the aluminium industry now constitutes 33% of world supply and is forecast to rise to 40% by 2025 (IAI, 2006b, Martcheck, 2006). Recycling is also an important energy saving factor in other non-ferrous metal industries, as well as the glass and plastics industries (GOI, various issues). Recycling occurs both internally within plants and externally in the waste management sector (See Section 10.4.5). 459
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Materials substitution, for example the addition of wastes (blast furnace slag, fly ash) and geo-polymers to clinker to reduce CO2 emissions from cement manufacture (See Section 7.4.5.1), is also applicable to the industrial sector. Some materials substitution options, for example the production of lightweight materials for vehicles, can increase GHG emissions from the industrial sector, which will be more than offset by the reduction of emissions from other sectors (See Section 7.4.9). Use of bio-materials is a special case of materials substitution. No projections of the GHG mitigation potential of this option were found in the literature. 7.3.7
Carbon dioxide Capture and Storage (CCS), including oxy-fuel combustion
CCS involves generating a stream with a high concentration of CO2, then either storing it geologically, in the ocean, or in mineral carbonates, or using it for industrial purposes. The IPCC Special Report on CCS (IPCC, 2005b) provides a full description of this technology, including its potential application in industry. It also discusses industrial uses of CO2, including its temporary retention in beverages, which are small compared to total industrial emissions of CO2. Large quantities of hydrogen are produced as feedstock for petroleum refining, and the production of ammonia and other chemicals. Hydrogen manufacture produces a CO2-rich by-product stream, which is a potential candidate for CCS technology. IPCC (2005b) estimated the representative cost of CO2 storage from hydrogen manufacture at 15 US$/tCO2 (55 US$/tC). Transport (250 km pipeline) injection and monitoring would add another 2 to 16 US$/tCO2 (7 to 60 US$/tC) to costs. CO2 emissions from steel making are also a candidate for CCS technology. IEA (2006a) estimates that CCS could reduce CO2 emissions from blast furnaces and DRI (direct reduction iron) plants by about 0.1 GtCO2 (0.03 GtC) in 2030 at a cost of 20 to 30 US$/tCO2 (73 to 110 US$/tC). Smelt reduction also allow the integration of CCS into the production of iron. CCS has also been investigated for the cement industry. Anderson and Newell (2004) estimate that it is possible to reduce CO2 emissions by 65 to 70%, at costs of 50 to 250 US$/tCO2 (183–917 US$/tC). IEA (2006a) estimates the potential for this application at up to 0.25 GtCO2 (0.07 GtC) in 2030. Oxy-fuel combustion can be used to produce a CO2-rich flue gas, suitable for CCS, from any combustion process. In the past, oxy-fuel combustion has been considered impractical because of its high flame temperature. However, Gross et al. (2003), report on the development of technology that allows oxy-fuel combustion to be used in industrial furnaces with conventional materials. Tests in an aluminium remelting furnace showed up to 73% reduction in natural gas use compared to a conventional air-natural gas furnace. When the energy required to produce oxygen is taken into account, overall energy saving is reduced to 50 to 60% (Jupiter Oxygen Corp., 2006). Lower but still 460
impressive energy efficiency improvements have been obtained in other applications, up to 50% in steel remelting furnaces, up to 45% in small glass-making furnaces, and up to 15% in large glass-making furnaces (NRC, 2001). The technology has also been demonstrated using coal and waste oils as fuel. Since much less nitrogen is present in the combustion chamber, NOx emissions are very low, even without external control, and the system is compatible with integrated pollution removal technology for the control of mercury, sulphur and particulate emissions as well as CO2 (Ochs et al., 2005). Industry does not currently use CCS as a mitigation option, because of its high cost. However, assuming that the R&D currently underway on lowering CCS cost is successful, application of this technology to industrial CO2 sources should begin before 2030 and be wide-spread after that date.
7.4 Process-specific technologies and measures This section discusses process specific mitigation options. Barriers to the implementation of these options are discussed in Section 7.6. The section focuses on energy intensive industries: iron and steel, non-ferrous metals, chemicals, petroleum refining, minerals (cement, lime and glass) and pulp and paper. IEA (2006a) reported that these industries (ex-petroleum refining) accounted for 72% of industrial final energy use in 2003. With petroleum refining, the total is about 85%. A subsection covers the food industry, which is not a major contributor to global industrial GHG emissions, but is a large contributor to these emissions in many developing countries. Subsections also cover other industries and inter-industry options, where the use of one industry’s waste as a feedstock or energy source by another industry can reduce overall emissions (See Section 7.4.9). All the industries discussed in this section can benefit from application of the sector-wide technologies (process optimization, energy efficiency, etc.) discussed in Section 7.3. The application of these technologies will not be discussed again. 7.4.1
Iron and steel
Steel is by far the world’s most important metal, with a global production of 1129 Mt in 2005. In 2004, the most important steel producers were China (26%), EU-25 (19%), Japan (11%), USA (10%) and Russia (6%) (IISI, 2005). Three routes are used to make steel. In the primary route (about 60%), used in almost 50 countries, iron ore is reduced to iron in blast furnaces using mostly coke or coal, then processed into steel. In the second route (about 35%), scrap steel is melted in electric-arc furnaces to produce crude steel that is further processed. This process uses only 30 to 40% of the energy of the primary route, with CO2 emissions reduction being a function of the source of electricity (De Beer et al., 1998). The remaining steel production (about 5%), uses natural gas to produce direct reduced iron (DRI). DRI
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cannot be used in primary steel plants, and is mainly used as an alternative iron input in electric arc furnaces, which can result in a reduction of up to 50% in CO2 emissions compared with primary steel making (IEA, 2006a). Use of DRI is expected to increase in the future (Hidalgo et al., 2005). Global steel industry CO2 emissions are estimated to be 1500 to 1600 MtCO2 (410 to 440 MtC), including emissions from coke manufacture and indirect emissions due to power consumption, or about 6 to 7% of global anthropogenic emissions (Kim and Worrell, 2002a). The total is higher for some countries, for example steel production accounts for over 10% of China’s energy use and about 10% of its anthropogenic CO2 emissions (Price et al., 2002). Emissions per tonne of steel vary widely between countries: 1.25 tCO2 (0.35 tC) in Brazil, 1.6 tCO2 (0.44 tC) in Korea and Mexico, 2.0 tCO2 (0.54 tC) in the USA, and 3.1 to 3.8 tCO2 (0.84 to 1.04 tC) in China and India (Kim and Worrell, 2002a). The differences are based on the production routes used, product mix, production energy efficiency, fuel mix, carbon intensity of the fuel mix, and electricity carbon intensity. Energy Efficiency. Iron and steel production is a combination of batch processes. Steel industry efforts to improve energy efficiency include enhancing continuous production processes to reduce heat loss, increasing recovery of waste energy and process gases, and efficient design of electric arc furnaces, for example scrap preheating, high-capacity furnaces, foamy slagging and fuel and oxygen injection. Continuous casting, introduced in the 1970s and 1980s, saves both energy and material, and now accounts for 88% of global steel production (IISI, 2005). Figure 7.1 shows the technical potential6 for CO2 emission reductions by region in 2030 for full diffusion of eight cost-effective and/or well developed energy savings technologies under the SRES B2 scenario, using a methodology developed by Tanaka et al. (2005, 2006). The potential for energy efficiency improvement varies based on the production route used, product mix, energy and carbon intensities of fuel and electricity, and the boundaries chosen for the evaluation. Tanaka et al. (2006) also used a Monte Carlo approach to estimate the uncertainty in their projections of technical potential for three steel making technologies. Kim and Worrell (2002a) estimated economic potential by taking industry structure into account. They benchmarked the energy efficiency of steel production to the best practice performance in five countries with over 50% of world steel production, finding potential CO2 emission reductions due to energy efficiency improvement varying from 15% (Japan) to 40% (China, India and the USA). While China has made significant improvements in energy efficiency, reducing energy consumption per tonne
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of steel from 29.3 GJ in 1990 to 23.0 GJ in 20007 (Price et al., 2002), there is still considerable potential for energy efficiency improvement and CO2 emission mitigation (Kim and Worrell, 2002a). Planned improvements include greater use of continuous casting and near-net shape casting, injection of pulverized coal, increased heat and energy recovery and improved furnace technology (Zhou et al., 2003). A study in 2000 estimated the 2010 global technical potential for energy efficiency improvement with existing technologies at 24% (De Beer et al., 2000a) and that an additional 5% could be achieved by 2020 using advanced technologies such as smelt reduction and near net shape casting. ULCOS (Ultra-Low CO2 Steel making), a consortium of 48 European companies and organizations, has as its goal the development of steel making technology that reduces CO2 emission by at least 50%. The technologies being evaluated, including CCS, biomass and hydrogen reduction, show a potential for controlling emissions to 0.5 to 1.5 tCO2/t (0.14 to 0.41 tC/t) steel (Birat, 2005). Economics may limit the achievable emission reduction potential. A study of the US steel industry found a 2010 technical potential for energyefficiency improvement of 24% (Worrell et al., 2001a), but economic potential, using a 30% hurdle rate, was only 18%, even accounting for the full benefits of the energy efficiency measures (Worrell et al., 2003). A similar study of the European steel industry found an economic potential of less than 13% (De Beer et al., 2001). These studies focused mainly on retrofit options. However, potential savings could be realized by a combination of capital stock turnover and retrofit of existing equipment. A recent analysis of the efficiency improvement of electric arc furnaces in the US steel industry found that the average efficiency improvement between 1990 and 2002 was 1.3%/yr, of which 0.7% was due to capital stock turnover and 0.5% due to retrofit of existing furnaces (Worrell and Biermans, 2005). Future efficiency developments will aim at further process Data is pluralintegration. The most important are near net shape casting (Martin et al., 2000), with current applications at numerous plants around the world; and smelt reduction, which integrates ore agglomeration, coke making and iron production in a single process, offering an energy-efficient alternative at small to medium scales (De Beer et al., 1998). Fuel Switching. Coal (in the form of coke) is the main fuel in the iron and steel industry because it provides both the reducing agent and the flow characteristics required by blast furnaces in the production of iron. Steel-making processes produce large volumes of byproducts (e.g., coke oven and blast furnace gas) that are used as fuel. Hence, a change in coke use will affect the energy balance of an integrated iron and steel plant.
See Section 2.4.3.1 for definitions of mitigation potential. China uses various indicators to present energy intensity, including “comprehensive” and “comparable” energy intensity. The indicators are not always easily comparable to energy intensities from other countries or regions. The above figures use the comparable energy intensity, which is a constructed indicator, making it impossible to compare to those of other studies. Only a detailed assessment of the energy data can result in an internationally comparable indicator (Price et al., 2002).
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Non-Annex 1 East Asia
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Figure 7.1: CO2 reduction potential of eight energy saving technologies in 2030 CDQ = Coke Dry Quenching, HS = Hot Stove, TRT = Top Pressure Recovery Turbine, SC = Sinter Cooling, CC = Continuous Casting, SP = Sinter Plant, BOFG = Basic Oxygen Furnace Gas, ME = Main Exhaust, WH = Waste Heat Note: B2 Scenario, CO2 emission reduction based on energy saving assuming 100% diffusion in 2030 less current diffusion rates. Source: Tanaka, 2006.
Technology enabling the use of oil, natural gas and pulverized coal to replace coke in iron-making has long been available. Use of this technology has been dictated by the relative costs of the fuels and the process limitations in iron-making furnaces. Use of oil and natural gas could reduce CO2 emissions. More recently, the steel industry has developed technologies that use wastes, such as plastics, as alternative fuel and raw materials 462
(Ziebek and Stanek, 2001). Pretreated plastic wastes have been recycled in coke ovens and blast furnaces (Okuwaki, 2004), reducing CO2 emissions by reducing emissions from incineration and the demand for fossil fuels. In Brazil, charcoal is used as an alternative to coke in blast furnaces. While recent data are not available, use of charcoal declined in the late 1990s, as merchant coke became cheaper (Kim and Worrell,
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2002a). The use of hydrogen to reduce iron ore is a longer-term technology discussed in Section 7.12. CCS is another longerterm technology that might be applicable to steel making (see section 7.3.7). 7.4.2
Non-ferrous metals
The commercially relevant non-ferrous metals and specific and total CO2 emissions from electrode and reductant use are shown in Table 7.6. Annual production of these metals ranges from approximately 30 Mt for aluminium to a few hundred kilotonnes for metals and alloys of less commercial importance. Production volumes are fairly low compared to some of the world’s key industrial materials like cement, steel, or paper. However, primary production of some of these metals from ore can be far more energy intensive. In addition, the production of these metals can result in the emission of high-GWP GHGs, for example PFCs in aluminium or SF6 in magnesium, which can add significantly to CO2-eq emissions. Generally, the following production steps need to be considered: mining, ore refining and enrichment, primary smelting, secondary smelting, metal refining, rolling and casting. For most non-ferrous metals, primary smelting is the most energy-intensive step, but significant levels of emissions of fluorinated GHGs have been reported from the refining and casting steps. 7.4.2.1
Aluminium
Global primary aluminium production was 29.9 Mt in 2004 (IAI, 2006b) and has grown an average of 5% per year over the last ten years. Production is expected to grow by 3% per year for the next ten years. Recycled aluminium production was approximately 14 Mt in 2004 and is also expected to double by 2020 (Marchek, 2006). Primary aluminium metal (Al) is produced by the electrolytic reduction of alumina (Al2O3) in a highly energy-intensive process. In addition to the CO2 emissions associated with electricity generation, the process itself is GHG-intensive. It involves a reaction between Al2O3 and a carbon anode: 2 Al2O3 + 3 C = 4 Al + 3 CO2. In the electrolysis cell, Al2O3 is dissolved in molten cryolite (Na3AlF6). If the flow of Al2O3 to the anode is lower than required, cryolite will react with the anode to form PFCs, CF4 and C2F6 (IAI, 2001). CF4 has a GWP8 of 6500 and C2F6, which accounts for about 10% of the mix, has a GWP of 9200 (IPCC, 1995). These emissions can be significantly reduced by careful attention to operating procedures and more use of computer-control. Even larger reductions in emissions can be achieved by upgrading older cell technology (for example., Vertical Stud Södeberg or Side Worked Prebake) by addition of point feeders to better control alumina feeding. The
8
Table 7.6: Emission factors and estimated global emissions from electrode use and reductant use for various non-ferrous metals CO2 emissions (tCO2/t product)
Global CO2 emissions (ktCO2)
Primary aluminium
1.55
44,700
Ferrosilicon
2.92
10,500
Ferrochromium
1.63
9,500
Silicomanganese
1.66
5,800
Calcium carbide
1.10
4,475
Magnesium
0.05
4,000
Silicon metal
4.85
3,500
Lead
0.64
3,270
Zinc
0.43
3,175
Others Total
6,000 91,000
Note: Indirect emissions and non-CO2 greenhouse-gas emissions are not included. Source: Sjardin, 2003.
cost of such a retrofit can be recovered through the improved productivity. Use of the newer technologies, which require a major retrofit, can cost up to 27 US$/tCO2-eq (99 US$/tC-eq) (US EPA, 2006a). Members of the International Aluminium Institute (IAI), responsible for more than 70% of the world’s primary aluminium production, have committed to an 80% reduction in PFC emissions intensity for the industry as a whole, and to a 10% reduction in smelting energy intensity by 2010 compared to 1990 for IAI member companies. IAI data (IAI, 2006a) shows a reduction in CF4 emissions intensity from 0.60 to 0.16 kg/t Al, and a reduction in C2F6 emissions intensity from 0.058 to 0.016 kg/t Al between 1990 and 2004, with best available technology having a median emission rate of only 0.05 kg CF4/t in 2004. Overall, PFC emissions from the electrolysis process dropped from 4.4 to 1.2 tCO2-eq/t (1.2 to 0.3 tC-eq/t) Al metal produced. IAI data (IAI, 2006b) show a 6% reduction in smelting energy use between 1990 and 2004. Benchmarking has been used to identify opportunities for emission reductions. The steps taken to control these emissions have been mainly low or no-cost, and have commonly been connected to smelter retrofit, conversion, or replacements (Harnisch et al., 1998; IEA GHG 2000). However, much of the 30% of production from non-IAI members still uses older technology (EDGAR, 2005). SF6 (GWP = 23,900 (IPCC, 1995)) has been used for stirring and degassing of molten aluminium in secondary smelters and foundries (Linde, 2005). The process is not very common
The Global Warming Potentials used in this chapter are those used for national inventory reporting under the UNFCCC. They are the 100-year values reported in the IPCC Second Assessment Report (IPCC, 1995).
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Table 7.7: Greenhouse-gas emission from production of various non-ferrous metals Global emissions (MtCO2-eq/yr)
Source and year
CO2 - Mining and refining
109
IEA GHG, 2000 for 1995
CO2 - Electrodes
48
IAI, 2006b for 2004
Metal Aluminium
PFC - Emissions
69
EDGAR, 2005 for 2000
CO2 - Electricity
300
IEA GHG, 2001 for 1995
Magnesium CO2 - Electrode and cell-feed
4
Sjardin, 2003 for 1995
SF6 - Production and casting
9
US EPA, 2006b for 2000
CO2 - Electricity
Unknown
CO2 - Other steps in the production process
Unknown
All other non-ferrous metals CO2 - Process CO2 - Electricity CO2 - Other steps All non-ferrous metals
40
Unknown Approximately 500 (lower bound)
because of cost and technical problems (UBA, 2004). Current level of use is unknown, but is believed to be much smaller than SF6 used in magnesium production. The main potentials for additional CO2-eq emission reductions are a further penetration of state-of-the-art, point feed, prebake smelter technology and process control plus an increase of recycling rates for old-scrap (IEA GHG, 2001). Research is proceeding on development of an inert anode that would eliminate anode-related CO2 and PFC emissions from Al smelting. A commercially viable design is expected by 2020 (The Aluminium Association, 2003). However, IEA (2006a) notes that the ultimate technical feasibility of inert anodes has yet to be proven, despite 25 years of research. 7.4.2.2
Magnesium
Magnesium, produced in low volumes, is very energy intensive. Its growth rate has been high due to increasing use of this lightweight metal in the transport industry. SF6 is quite commonly used as cover gas for casting the primary metal into ingots and for die casting magnesium. Estimates of global SF6 emissions from these sources in 2000 range from about 9 MtCO2-eq (2.4 MtC-eq) (US EPA, 2006a), to about 20 MtCO2eq (5.5 MtC-eq) (EDGAR, 2005). The later value is about equal to energy related emissions from the production of magnesium. Harnisch and Schwarz (2003) found that the majority of these emissions can be abated for <1.2 US$/tCO2-eq (<4.4 US$/tCeq) by using SO2, the traditional cover gas, which is toxic and corrosive, or using more advanced fluorinated cover gases with low GWPs. US EPA (2006a) report similar results. Significant parts of the global magnesium industry located in Russia and 464
Sjardin, 2003
Unknown
China still use SO2 as a cover gas. The International Magnesium Association, which represented about half of global magnesium production in 2002, has committed its member companies to phasing out SF6 use by 2011 (US EPA, 2006a). 7.4.2.3
Total emissions and reduction potentials
Table 7.7 gives the lower bounds for key emission sources in the non-ferrous metal industry. Total annual GHG gas emissions from the non-ferrous metal industry were at least 500 MtCO2-eq (140 MtC-eq) in 2000. The GHG abatement options for the production of non-ferrous metals other than aluminium are still fairly uncertain. In the past, these industries have been considered too small or too complex regarding raw materials, production technologies and product qualities, to be systematically assessed for reduction options. 7.4.3
Chemicals and fertilizers
The chemical industry is highly diverse, with thousands of companies producing tens of thousands of products in quantities varying from a few kilograms to thousand of tonnes. Because of this complexity, reliable data on GHG emissions is not available (Worrell et al., 2000a). The majority of the CO2eq direct emissions from the chemical industry are in the form of CO2, the largest sources being the production of ethylene and other petrochemicals, ammonia for nitrogen-based fertilizers, and chlorine. These emissions are from both energy use and from venting and incineration of byproducts. In addition, some chemical processes create other GHGs as byproducts, for example N2O from adipic acid, nitric acid and caprolactam manufacture; HFC-23 from HCFC-22 manufacture; and very
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small amounts of CH4 from the manufacture of silicon carbide and some petrochemicals. Pharmaceutical manufacture uses relatively little energy, most of which is used in the buildings that house industrial facilities (Galitsky and Worrell, 2004).
GJ (LHV)/t of ammonia 70 actual data 60
10 best-in-class facilities in 2004 IFA benchmarking survey
50
The chemical industry makes use of many of the sectorwide technologies described in Section 7.3. Much of the petrochemical industry is co-located with petroleum refining, creating many opportunities for process integration and cogeneration of heat and electricity. Both industries make use of the energy in byproducts that would otherwise be vented or flared, contributing to GHG emissions. Galitsky and Worrell (2004) identify separations, chemical synthesis and process heating as the major energy consumers in the chemical industry, and list examples of technology advances that could reduce energy consumption in each area, for example improved membranes for separations, more selective catalysts for synthesis and greater process integration to reduce process heating requirements. Longer-term, biological processing offers the potential of lower energy routes to chemical products (See Section 7.12.1). 7.4.3.1
Ethylene
Ethylene, which is used in the production of plastics and many other products, is produced by steam cracking hydrocarbon feedstocks, from ethane to gas oil. Hydrogen, methane, propylene and heavier hydrocarbons are produced as byproducts. The heavier the feedstock, the more and heavier the byproducts, and the more energy consumed per tonne of ethylene produced (Worrell et al., 2000a). Ren et al. (2006) report that steam cracking for olefin production is the most energy consuming process in the chemicals industry, accounting for emissions of about 180 MtCO2/yr (49MtC/yr), but that significant reductions are possible. Cracking consumes about 65% of the total energy used in ethylene production, but use of state-of-the-art technologies (e.g., improved furnace and cracking tube materials and cogeneration using furnace exhaust) could save up to about 20% of total energy. The remainder of the energy is used for separation of the ethylene product, typically by low-temperature distillation and compression. Up to 15% total energy can be saved by improved separation and compression techniques (e.g., absorption technologies for separation). Catalytic cracking also offers the potential for reduced energy use, with a savings of up to 20% of total energy. This savings is not additional to the energy savings for improved steam cracking (Ren et al., 2006). Processes have been developed for converting methane in natural gas to olefins as an alternative to steam cracking. However, Ren et al. (2005) conclude that the most efficient of these processes uses more than twice as much primary energy as state-of-the-art steam cracking of naphtha. 7.4.3.2
Fertilizer manufacture
Swaminathan and Sukalac (2004) report that the fertilizer industry uses about 1.2% of world energy consumption and is
average of 66 plants covered in 2004 IFA benchmarking survey
40 30 20
thermodynamic limit 10 1955
1965
1975
1985
1995
2005
Figure 7.2: Design energy consumption trends in world ammonia plants Sources: Chaudhary, 2001; PSI, 2004.
responsible for about the same share of global GHG emissions. More than 90% of this energy is used in the production of ammonia (NH3). However, as the result of energy efficiency improvements, modern ammonia plants are designed to use about half the energy per tonne of product than those designed in 1960s, (see Figure 7.2), with design energy consumption dropping from over 60 GJ/t NH3 in the 1960s to 28 GJ/t NH3 in the latest design plants, approaching the thermodynamic limit of about 19 GJ/t NH3, and limiting scope for further efficiency increases. Benchmarking data indicate that the best-in-class performance of operating plants ranges from 28.0 to 29.3 GJ/t NH3 (Chaudhary, 2001; PSI, 2004). The newest plants tend to have the best energy performance, and many of them are located in developing countries, which now account for 57% of nitrogen fertilizer production (IFA, 2004). Individual differences in energy performance are mostly determined by feedstock (natural gas compared with heavier hydrocarbons) and the age and size of the ammonia plant (PSI, 2004, Phylipsen et al., 2002). National and regional averages are strongly influenced by whether the sector has undergone restructuring, which tends to drive less efficient producers out of the market (Sukalac, 2005). Ammonia plants that use natural gas as a feed-stock have an energy efficiency advantage over plants that use heavier feedstock’s and a high percentage of global ammonia capacity already is based on natural gas. China is an exception in that 67% of its ammonia production is based on coal (CESP, 2004) and small-scale plants account for 90% of the coal-based production. The average energy intensity of Chinese coal-based production is about 53 GJ/t, compared with a global average of 41.4 GJ/t (Giehlen, 2006). Retrofit of old plants is feasible and offers a potential for improved efficiency. Verduijn and de Wit (2001) concluded that the energy efficiency of large single train ammonia plants, the bulk of existing capacity, could be improved at reasonable cost to levels approaching newly designed plants, provided that the upgrading is accompanied by an increase in capacity. 465
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Significant reductions of CO2 emissions, below those achieved by state-of-the-art ammonia plants, could be achieved by using low-carbon or carbon-free hydrogen, which could be obtained through the application of CCS technology (see Section 7.3.7), biomass gasification, or electrolysis of water using electricity from nuclear or renewables. About half the ammonia produced for fertilizer is reacted with CO2 to form urea (UNIDO and IFDC, 1998), but the CO2 is released when the fertilizer is applied. However, this use of CO2 reduces the potential for applying CCS technology. 7.4.3.3
Chlorine manufacture
The TAR (IPCC, 2001a) reported on the growing use of more energy-efficient membrane electrolysis cells for chlorine production. There have been no significant developments affecting GHG emissions from chlorine production since the TAR. 7.4.3.4
N2O emissions from adipic acid, nitric acid and caprolactam manufacture
N2O emissions from nitric and adipic acid plants account for about 5% of anthropogenic N2O emissions. Due to significant investment in control technologies by industry in North America, Japan and the EU, worldwide emissions of N2O (GWP = 310 (IPCC,1995)) from adipic and nitric acid production decreased by 30%, from 223 MtCO2-eq (61 MtC-eq) in 1990 to 154 MtCO2-eq (42 MtC-eq) in 2000 (US EPA 2006b). Some of the reduction was due to the installation of NO control technology to meet regulatory requirements. By 2020, global emission from the manufacture of adipic acid and from the manufacture of nitric acid are projected to grow to 177 MtCO2-eq (48 MtCeq). Developed nations account for approximately 55% of emissions in both 2000 and 2020 (US EPA, 2006b). Experience in the USA, Japan and the EU shows that thermal destruction can eliminate 96% of the N2O emitted from an adipic acid plant. Catalytic reduction can eliminate 89% of the N2O emitted from a typical nitric plant in a developed country (US EPA, 2006a). Mitigation potential at nitric acid plants can range from 70% to almost 100% depending on the catalyst and plant operating conditions (US EPA, 2001, Continental Engineering BV, 2001). Costs range from 2.0 to 5.8 US$/tCO2-eq (7.3 to 21.2 US$/tCeq) (2000 US$) using a 20% discount rate and a 40% corporate tax rate, and a maximum mitigation potential of 174 MtCO2-eq (44 MtC-eq) is projected in 2030. Global N2O emissions from caprolactam production in 2000 were estimated at 10 to 15 MtCO2-eq (2.7 to 4.1 MtC) (EDGAR, 2005). IPCC (2006) indicates that these emissions can be controlled to a high degree by non-specific catalytic reduction. 7.4.3.5
HFC-23 emissions from HCFC-22 manufacture
On average, 2.3% HFC-23 (GWP = 11,700 (IPCC, 1995)) is produced as a byproduct of HCFC-22 manufacture. The EDGAR 466
database estimated 2000 emissions at 78 MtCO2-eq (21 MtCeq) (EDGAR, 2005), while the US EPA estimated 96 MtCO2-eq (26 MtC-eq) (US EPA, 2006a). HCFC-22 has been used as a refrigerant, but under the Montreal Protocol its consumption is scheduled to end by 2020 in developed countries and over a longer period in developing countries. However, production of HCFC-22 for use as a feedstock in the manufacture of fluoropolymers, plastics and HFCs is expected to grow, leading to increasing emissions through 2015 in the business-as-usual case. Data on production rates and control technologies are contained in the IPCC Special Report on Safeguarding the Ozone Layer and the Global Climate System (IPCC/TEAP, 2005). Capture and destruction by thermal oxidation is a highly effective option for reducing HFC-23 emissions at a cost of less than 0.20 to 0.35 US$/tCO2-eq (0.75 to 1.20 US$/tC-eq) (IPCC/TEAP, 2005, US EPA, 2006a). 7.4.4
Petroleum refining
As of the beginning of 2004, there were 735 refineries in 128 countries with a total crude oil distillation capacity of 82.3 million barrels per day. The U.S (20.5%), EU-25 (16.4%), Russia (6.6%), Japan (5.7%) and China (5.5%) had the largest shares of this capacity (EIA, 2005). Petroleum industry operations consume up to 15 to 20% of the energy in crude oil, or 5 to 7% of world primary energy, with refineries consuming most of that energy (Eidt, 2004). Comparison of energy or CO2 intensities among countries is not practical because refining energy use is a complex function of crude and product slates and processing equipment. Simple metrics (e.g., energy consumed/barrel refined) do not account for that complexity. The shifts towards heavier crude and lower sulphur products will increase refinery energy use and CO2 emissions. One study indicated that the combination of heavier crude and a 10 ppm maximum gasoline and diesel sulphur content would increase European refinery CO2 emissions by about 6% (CONCAWE, 2005). Worrell and Galitsky (2005), based on a survey of US refinery operations, found that most petroleum refineries can economically improve energy efficiency by 10–20%, and provided a list of over 100 potential energy saving steps. Key items included: use of cogeneration, improved heat integration, combustion optimization, control of compressed air and steam leaks and use of efficient electrical devices. The petroleum industry has had long-standing energy efficiency programmes for refineries and the chemical plants with which they are often integrated. These efforts have yielded significant results. Exxon Mobil reported over 35% reduction in energy use in its refineries and chemical plants from 1974 to 1999, and in 2000 instituted a programme whose goal was a further 15% reduction, which would reduce emissions by an additional 12 MtCO2/yr. (Eidt, 2004). Chevron (2005) reported a 24% reduction in its index of energy use between 1992 and 2004. Shell (2005) reported energy efficiency improvements of 3 to 7% at its refineries and chemical plants. Efficiency improvements are expected to continue as technology improves and energy prices rise.
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Refineries typically use a wide variety of gaseous and liquid byproducts as fuel. Byproducts that are not used as fuel are flared. Reducing the amount of material flared will increase refinery energy efficiency and decrease CO2 emissions, and has become an objective for refinery management worldwide, though flare reduction projects are often undertaken to reduce local environmental impacts Munn (2004). No estimate of the incremental reduction in CO2 emissions is available. Refineries use hydrogen to remove sulphur and other impurities from products, and to process heavy hydrocarbons into lighter components for use in gasoline and distillate fuels. The hydrogen is supplied from reformer gas, a hydrogen-rich byproduct of catalytic reforming, and a process for upgrading gasoline components. If this source is insufficient for the refinery’s needs, hydrogen is manufactured by gasification of fossil fuels. US refineries use about 4% of their energy input to manufacture hydrogen (Worrell and Galitsky, 2005). Hydrogen production produces a CO2-rich stream, which is a candidate for CCS (see Section 7.3.7). 7.4.5
Minerals
7.4.5.1
Cement
Cement is produced in nearly all countries. Cement consumption is closely related to construction activity and to general economic activity. Global cement production grew from 594 Mt in 1970 to 2200 Mt in 2005, with the vast majority of the growth occurring in developing countries. In 2004 developed countries produced 570 Mt (27% of world production) and developing countries 1560 Mt (73%) (USGS, 2005). China has almost half the world’s cement capacity, manufacturing an estimated 1000 Mt in 2005 (47% of global production), followed by India with a production of 130 Mt in 2005 (USGS, 2006). Global cement consumption is growing at about 2.5%/yr. The production of clinker, the principal component of cement, emits CO2 from the calcination of limestone. Cement production is also highly energy-intensive. The major energy uses are fuel for the production of clinker and electricity for grinding raw materials and the finished cement. Coal dominates in clinker making. Based on average emission intensities, total emissions in 2003 are estimated at 1587 MtCO2 (432 MtC) to 1697 MtCO2 (462 MtC), or about 5% of global CO2 emissions, half from process emissions and half from direct energy use. Global average CO2 emission per tonne cement production is estimated by Worrell et al. (2001b) at 814 kg (222 kg C), while Humphreys and Mahasenan (2002) estimated 870 kg (264 kg C). CO2 emission/t cement vary by region from a low of 700 kg (190 kg C) in Western Europe and 730 kg (200 kg C) in Japan and South Korea, to a high of 900, 930, and 935 kg (245, 253 and 255 kg C) in China, India and the United States (Humphreys and Mahasenan, 2002; Worrell et al., 2001b). The differences in
emission intensity are due (in order of contribution) to differences in the clinker content of the cement produced, energy efficiency, carbon intensity of the clinker fuel and carbon intensity of power generation (Kim and Worrell, 2002b). Emission intensities have decreased by approximately 0.9%/yr since 1990 in Canada, 0.3%/yr (1970–1999) in the USA, and 1%/yr in Mexico (Nyboer and Tu, 2003; Worrell and Galitsky, 2004; Sheinbaum and Ozawa, 1998). A reduction in energy intensity in India since 1995–1996 has led to a reduction in emissions from the industry despite the increase in output (Dasgupta and Roy, 2001). Analysis of CO2 emission trends in four major cement-producing countries showed that energy efficiency improvement and reduction of clinker content in cement were the main factors contributing to emission reduction, while the carbon intensity of fuel mix in all countries increased slightly. Both energy-related and process CO2 emissions can be reduced. The combined technical potential of these opportunities is estimated at 30% globally, varying between 20 and 50% for different regions (Humphreys and Mahasenan, 2002; Kim and Worrell, 2002b). Energy efficiency improvement has historically been the main contributor to emission reduction. Benchmarking and other studies have demonstrated a technical potential for up to 40% improvement in energy efficiency (Kim and Worrell, 2002b; Worrell et al., 1995). Countries with a high potential still use outdated technologies, like the wet process clinker kiln. Studies for the USA identified 30 opportunities in every production step in the cement-making process and estimated the economic potential for energy efficiency improvement in the US cement industry at 11%, reducing emissions by 5% (Worrell et al., 2000b; Worrell and Galitsky, 2004). The cement industry is capital intensive and equipment has a long lifetime, limiting the economic potential in the short term. The clinker kiln is an ideal candidate for the use of a wide variety of fuels, including waste-derived fuels, such as tyres, plastics, biomass, municipal solid wastes and sewage sludge (see Section 7.3.2). Section 7.3.7 discusses the potential for applying CCS in the cement industry. Standard Portland cement contains 95% clinker. Clinker production is responsible for the process emissions and most of the energy-related emissions. The use of blended cement, in which clinker is replaced by alternative cementitious materials, for example blast furnace slag, fly ash from coal-fired power stations, and natural pozzolanes, results in lower CO2 emissions (Josa et al., 2004). Humphreys and Mahasenan (2002) and Worrell et al. (1995) estimate the potential for reduction of CO2 emissions at more than 7%. Current use of blended cement is relatively high in continental Europe and low in the USA and UK. Alternatives for limestone-based cement are also being investigated (Gartner, 2004; Humphreys and Mahasenan, 2002). Geopolymers have been applied in niche markets, but have yet to be proven economical for large-scale application.
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7.4.5.2
Chapter 7
Lime
7.4.5.3
Glass
Generally lime refers both to high-calcium and dolomitic forms containing magnesium. Lime is produced by burning limestone or dolomite in small-scale vertical or large-scale rotary kilns. While in most industrialized countries the industry is concentrated in a small number of larger corporations, in most developing countries lime kilns are small operations using local technology. Even in industrialized countries like Greece there are independent small-scale vertical kilns in operation. Pulp and sugar mills may have captive lime production to internally regenerate lime. Lime is mainly used in a small number of industries (especially steel, but also chemicals, paper and sugar), mining, as well as for flue gas desulphurization. There are no detailed statistics on global lime production, however Miller (2003) estimated global production at 120 Mt, excluding regenerated lime. The largest producers are China, the USA, Russia, Germany, Mexico and Brazil.
Glass is produced by melting raw materials (mainly silica, soda ash and limestone), and often cullet (recycled glass), in glass furnaces of different sizes and technologies. Typical furnace designs include: cross-fired or end-fired with regenerative air preheat, recuperative heat recovery and fuel-oxygen firing (EUBREF Glass, 2001). The industry is capital intensive, furnaces have a lifetime of up to 12 years and there are a limited number of technology providers. Natural gas and fuel oil are the main fuels used by the glass industry. Reliable international statistics on glass production are not available. The global glass industry is dominated by the production of container glass and flat glass. According to industry estimates the global production of container glass was 57 Mt in 2001 (ISO, 2004); production of flat glass was 38 Mt in 2004 (Pilkington, 2005). The production volumes of special glass, domestic glass, mineral wool and glass fibres are each smaller by roughly an order of magnitude.
Process CO2 emissions from the calcination of limestone and dolomite are a function of the amounts of calcium carbonate, magnesium carbonate and impurity in the feedstock, and the degree of calcination. Theoretical process emissions are 785 kg CO2/t (214 kgC/t) calcium oxide and 1092 kg CO2/t (298 kgC/t) magnesium oxide produced. Energy use emissions are a function of the efficiency of the process, the fuel used, and indirect emissions from the electric power consumed in the process. In efficient lime kilns about 60% of the emissions are due to de-carbonisation of the raw materials. No estimates of global CO2 emissions due to lime production are available. In Europe process emissions are estimated at 750 kg CO2/t (205 kgC/t) lime (IPPC, 2001). For some applications, lime is recarbonated, mitigating part of the emissions generated in the lime industry. Regeneration of lime in pulp and sugar mills does not necessarily lead to additional CO2 emissions, as the CO2 is from biomass sources (Miner and Upton, 2002). Emissions from fuel use vary with the kiln type, energy efficiency and fuel mix. Energy use is 3.6 to 7.5 GJ/t lime in the EU (IPPC, 2001), 7.2 GJ/t in Canada (CIEEDAC, 2004) and for lime kilns in US pulp mills (Miner and Upton, 2002), and up to 13.2 GJ/t for small vertical kilns in Thailand (Dankers, 1995). In Europe, fuel-related emissions are estimated at 0.2 to 0.45 tCO2/t (0.05 to 0.12 tC/t) lime (IPPC, 2001). Electricity use for lime production is 40 to 140 kWh/t lime, depending on the type of kiln and the required fineness of the lime (IPPC, 2001).
Beerkens and van Limpt (2001) report the energy intensity of continuous glass furnaces in Europe and the USA as 4 to 10 GJ/t of container glass and 5 to 8.5 GJ/t of flat glass, depending on the size and technology of the furnace and the share of cullet used. The energy consumption for batch production is higher, typically 12.5 to 30 GJ/t of product (Römpp, 1995). Assuming an average energy use of 7 GJ/t of product, half from natural gas and half from fuel oil, yields an emission factor of 450 kg energy related CO2/t of product. Globally, energy used in the production of container and flat glass results in emissions of approximately 40 to 50 MtCO2 (11 to 14 MtC) per year. Emissions from the decarbonisation of soda ash and limestone can contribute up to 200 kg CO2/t (55 kgC/t) of product depending on the composition of the glass and the amount of cullet used (EU-BREF Glass, 2001).
Emission reductions are possible by use of more efficient kilns (Dankers, 1995; IPPC, 2001) and through improved management of existing kilns, using similar techniques to the cement industry (see Section 7.4.5.1). Switching to low-fossil carbon fuels can further reduce CO2 emissions. The use of solar energy has been investigated for small-scale installations (Meier et al., 2004). It may also be possible to reduce lime consumption in some processes, for example the sugar industry (Vaccari et al., 2005).
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The mid-term emission potential for energy efficiency improvements is less than half of what corresponds to the range of efficiencies reported by Beerkens and van Limpt (2001), which also reflect differences in product quality and furnace age. The global potential for emissions reduction from fuel switching is unknown. The main mitigation options in the industry include: improved process control, increased use (up to 100%) of cullet (Kirk-Othmer, 2005), increased furnace size, use of regenerative heating, oxy-fuel technology, batch and cullet pre-heating, reduction of reject rates (Beerkens and van Limpt, 2001), use of natural gas instead of fuel oil, and CO2 capture for large oxy-fuel furnaces. High caloric value biogas could be used to reduce net CO2 emissions, but potential new break-through technologies are not in sight. 7.4.5.4
Ceramics
The range of commercial ceramics products is large and includes bricks, roof, wall and floor tiles, refractory ceramics, sanitary ware, tableware and cookware and other products. In terms of volume, the production of bricks and tiles dominate.
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The main raw materials used in the brick industry include clay and kaolin. Production technologies and respective energy efficiencies vary tremendously from large industrial operations to cottage and artisan production, which are still very common in many developing countries. The main fuels used in modern industrial kilns are natural gas and fuel oil. Specific energy consumption varies considerably for different products and kiln designs. The EU-BREF Ceramics (2005) reported specific energy consumptions for modern industrial brick production of 1.4 to 2.4 GJ/t of product. Small-scale kilns – used mainly for brick production – are often used in developing countries. Wood, agricultural residues and coal (FAO, 1993) are the main fuels used, with specific energy consumptions of 0.8 to 2.8 GJ/t of brick for the smallto medium sized kilns, and 2 to 8 GJ/t of brick for the very small-scale kilns used by cottage industries and artisans (FAO, 1993). Producers also utilize the energy contained in the organic fraction of clay and shale as well as in pore forming agents (e.g., sawdust) added to the clay in the production process. CO2 emissions from the calcination of carbonates contained in clay and shale typically contribute 20 to 50% of total emissions. The current choices of building materials and kiln technologies are closely related to local traditions, climate, and the costs of labour, capital, energy and transport, as well as the availability of alternative fuels, raw materials and construction materials. Reliable international statistics on the production of ceramics products are not available. Consumption of bricks, tiles and other ceramic products in tonnes per capita per year is estimated at 1.2 in China (Naiwei, 2004); 0.4 in the EU (EU-BREF Ceramics, 2005), 0.1 in the USA (USGS, 2005), and 0.25, 0.12, and 0.05 for Pakistan, India and Bangladesh (FAO, 1993). This suggests that the global production of ceramic products exceeds 2 Gt/yr, leading to the emission of more than 400 MtCO2 (110 MtC) per year from energy use and calcination of carbonates. Additional research to better understand the emission profile and mitigation options for the industry is needed. GHG mitigation options include the use of more efficient kiln design and operating practices, fuel switching from coal to fuel oil, natural gas and biomass, and partial substitution of clay and shale by alternative raw materials such as fly ash. Mitigation options could also include the use of alternative building materials such as wood or bricks made from lime and sand. However, emissions over the whole life cycle of the products including their impact on the energy performance of the building need to be considered. 7.4.6
Pulp and paper
The pulp and paper industry is a highly diverse and increasing global industry. In 2003, developing countries produced 26% of paper and paperboard and 29% of global wood products; 31% of paper and paperboard output was traded internationally (FAOSTAT, 2006). Direct emissions from the pulp, paper,
paperboard and wood products industries are estimated to be 264 MtCO2/yr (72 MtC/yr) (Miner and Lucier, 2004). The industry’s indirect emissions from purchased electricity are less certain, but are estimated to be 130 to 180 MtCO2/yr (35 to 50 MtC/yr) (WBCSD, 2005). 7.4.6.1
Mitigation options
Use of biomass fuels: The pulp and paper industry is more reliant on biomass fuels than any other industry. In developed countries biomass provides 64% of the fuels used by wood products facilities and 49% of the fuel used by pulp, paper and paperboard mills (WBCSD, 2005). Most of the biomass fuel used in the pulp and paper industry is spent pulping liquor, which contains dissolved lignin and other materials from the wood that are not used in paper production. The primary biomass fuel in the wood-products sector is manufacturing residuals that are not suitable for use as byproducts. Use of combined heat and power: In 2002, the pulp and paper industry used cogeneration to produce 40% of its electricity requirements in the USA (US DOE, 2002) and over 30% in the EU (CEPI, 2001), and that use continues to grow. Black liquor gasification: Black liquor is the residue from chemical processing to produce wood pulp for papermaking. It contains a significant amount of biomass and is currently being burned as a biomass fuel. R&D is underway on gasification of this material to increase the efficiency of energy recovery. Gasification could also create the potential to produce synfuels and apply CCS technology. IEA (2006a) estimates a 10 to 30 MtCO2 (2.7 to 8.1 MtC) mitigation potential for this technology in 2030. While gasification would increase the energy efficiency of pulp and paper plants, the industry as a whole would not become a net exporter of biomass energy (Farahani et al., 2004). Recycling: Recovery rates for waste paper (defined as the percentage of domestic consumption that is collected for reuse) in developed countries are typically at least 50% and are over 65% in Japan and parts of Europe (WBCSD, 2005). Globally, the utilization rate (defined as the fraction of fibre feedstock supplied by recovered fibre) was about 44% in 2004 (IEA, 2006a). The impact of this recycling is complex, affecting the emissions profile of paper plants, forests and landfills. A number of studies examine the impacts of recycling on life-cycle GHG emissions (Pickens et al., 2002, Bystrom and Lonnstedt, 1997). These and other studies vary in terms of boundary conditions and assumptions about end-of-life management, and none attempt to examine potential indirect impacts of recycling on market-based decisions to leave land in forest rather than convert it to other uses. Although most (but not all) of these studies find that paper recycling reduces life-cycle emissions of GHG compared to other means of managing used paper, the analyses are dependent on study boundary conditions and site-specific factors and it is not yet 469
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possible to develop reliable estimates of the global mitigation potential related to recycling. However, both the USA (US EPA, 2002) and EU (EC, 2004) identify paper recycling as a GHG emissions reduction option. 7.4.6.2
Food
Most food industry products are major commercial commodities, particularly for developing countries, and are quite energy-intensive. The most important products from a climate perspective are sugar, palm oil, starch and corn refining, since these can be a source of fuel products. The sugar cane industry produces 1.2 Gt sugar/yr. (Banda, 2002) from about 1670 mills, mostly located in tropical developing countries (Sims, 2002). Edible oils are another significant product, the exports of which support many developing country economies. Malaysia, the world’s largest producer and exporter of palm oil, has 3.5 Mha under palm oil production (UNDP, 2002), whilst Sri Lanka, the world’s fourth largest producer of coconut oils, has 0.4 Mha under cultivation (Kumar et al., 2003). Corn refining, including wet corn milling, has been the fastest growing market for US agriculture over the past twenty years (CRA, 2002). Further growth is projected as a result of the demand for ethanol as an automotive fuel. Corn wet milling is the most energy-intensive food industry, using 15% of total US food industry energy (EIA, 2002). Over 100 technologies and 470
7.4.7.1
Production processes, emissions and emission intensities
Emission reduction potential
Because of increased use of biomass and energy efficiency improvements, the GHG emissions from the pulp and paper industry have been reduced over time. Since 1990, CO2 emission intensity of the European paper industry has decreased by approximately 25% (WBCSD, 2005), the Australian pulp and paper industry about 20% (A3P, 2006), and the Canadian pulp and paper industry over 40% (FPAC, n.d.). Fossil fuel use by the US pulp and paper industry declined by more than 50% between 1972 and 2002 (AF&PA, 2004). However, despite these improvements, Martin et al. (2000) found a technical potential for GHG reduction of 25% and a cost-effective potential of 14% through widespread adoption of 45 energysaving technologies and measures in the US pulp and paper industry. Möllersten et al. (2003) found that CO2 emissions from the Swedish pulp and paper industry could be reduced by 0.5 to 5.0 MtCO2/yr (0.14 to 1.4 MtC/yr) at negative cost using commercially available technologies, primarily by generating more biomass-based electricity to displace carbon-intensive electricity from the grid. The large variation in the results reflected varying assumptions about the carbon intensity of displaced electricity and the impacts of ‘industrial valuation’ compared with ‘societal valuation’ of capital. Inter-country comparisons of energy-intensity in the mid-1990s suggest that fuel consumption by the pulp and paper industry could be reduced by 20% or more in a number of countries by adopting best practices (Farla et al., 1997). 7.4.7
measures for improving energy efficiency of corn wet milling have been identified (Galitsky et al., 2003).
The main production processes for the food industry are almost identical, involving preparatory stages including crushing, processing/refining, drying and packaging. Most produce process residuals, which typically go to waste. Food production requires electricity, process steam and thermal energy, which in most cases are produced from fossil fuels. The major GHG emissions from the food industry are CO2 from fossil fuel combustion in boilers and furnaces, CH4 (GWP=21 (IPCC, 1995)) and N2O (GWP = 310 (IPCC, 1995)) from waste water systems. The largest source of food industry emissions is CH4 from waste water treatment, which could be recovered for energy generation. For example, the Malaysian palm oil industry emits an estimated 5.17 MtCO2-eq (1.4 MtC-eq) from open-ponding systems that could generate 2.25 GWh of electricity while significantly reducing GHG emissions (Yeoh, 2004). Emissions from the Thai starch industry (Cohen, 2001) are estimated at 370 ktCO2-eq/yr (101 ktC-eq/yr), 88% were from waste water treatment, 8% from combustion of fuel oil and 4% from grid electricity. Although individual food industry factory emissions are low, their cumulative effect is significant in view of the large numbers of factories in both developed and developing countries. Typical energy intensities estimated at about 11 GJ/t for edible oils, 5 GJ/t for sugar and 10 GJ/t for canning operations (UNIDO, 2002). 7.4.7.2
Mitigation opportunities
The most important mitigation opportunities to reduce food industry GHG emissions in the near- and medium-term include technology and processes related to good housekeeping and improved management, improvements in both cross-cutting systems (e.g., boilers, steam and hot water distribution, pumps, compressors and fans) and process-specific technologies, improved process controls, more efficient process designs and process integration (Galitsky et al., 2001), cogeneration to produce electricity for own use and export (Cornland, 2001), and anaerobic digestion of residues to produce biogas for electricity generation and/or process steam (Yeoh, 2004). These technologies were discussed in Section 7.3, but some specific food industry applications are presented below. In Brazil, electricity sales to the grid from bagasse cogeneration reached 1.6 TWh in 2005 from an installed capacity of 400 MW. This capacity is expected to increase to 1000 MW with implementation of a government-induced voluntary industry programme (Moreira, 2006). In India, the sugar industry has diversified into cogeneration of power and production of fuel ethanol. Cogeneration began in 1993–1994, and as of 2004 reached 680 MW. Full industry potential is estimated at 3500
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MW. In 2001, India instituted a mixed fuel programme requiring use of a 5% ethanol blend, which will create an annual demand for 500 M litres of ethanol (Balasubramaniam, 2005). Application of traditional boilers with improved combustion and CEST (Condensing Extraction Steam Turbines) in the southern African sugar industry could produce surpluses of 135 MW for irrigation purposes and 1620 MW for export to the national grid (Yamba and Matsika, 2003) in 2010. Sims (2002) found that if all 31 of Australia’s existing sugar mills were converted to CEST technology, they could generate 20 TWh/yr of electricity and reduce emissions by 16 MtCO2/yr (4.4 MtC/ yr), assuming they replaced coal-fired electricity generation. Gasifying the biomass and using it in combined cycle gas turbine could double the CO2 savings (Cornland, 2001). Proposed CDM projects in the Malaysian palm oil industry (UNDP, 2002), and the Thai starch industry (Cohen, 2001) demonstrated that use of advanced anaerobic methane reactors to produce electricity would yield a GHG emission reduction of 56 to 325 ktCO2eq/yr (15 to 90 MtC-eq/yr). Application of improved energy management practices in the coconut industry (Kumar et al., 2003) and bakery industry (Kannan and Boy, 2003) showed significant saving of 40 to 60 % in energy consumption for the former and a modest saving of 6.5% for the latter. In the long term, use of residue biomass generated from the food industry in state-of-the-art Biomass Integrated Gasifier Combined Cycle (BIG/CC) technologies, could double electricity generation and GHG savings compared to CEST technology (Yamba and Matsika, 2003; Cornland et al., 2001). Virtually all countries have environmental regulations of varied stringency, which require installations including the food industry to limit final effluent BOD (Biochemical Oxygen Demand) in the waste water before discharge into waterways. Such measures are compelling industries to use more efficient waste water treatment systems. The recently introduced EUdirective requiring Best Available Techniques (BAT) as a condition for environmental permits in the fruit and vegetable processing industry (Dersden et al., 2002) will compel EU industry in this sector to introduce improved waste water purification processes thereby reducing fugitive emissions due to anaerobic reactions. 7.4.8
Other industries
This section covers a selection of other industries with significant emissions of high GWP gases. While some analyses include all emissions of these gases in the industrial sector, this chapter will consider only those which actually occur in the industrial sector. Thus, HFC and PFC emissions from use of automotive and residential air conditioning are covered in Chapter 5, section 5.2.1 and Chapter 6, section 6.8.4 respectively. The manufacture of semiconductors, liquid crystal display and photovoltaic cells can result in the emissions of PFCs, SF6, NF3 and HFC-23 (IPCC, 2006). The technology available to
reduce these emissions from semiconductor manufacturing, and the World Semiconductor Council (WSC) commitment to reduce PFC emissions by at least 10% by 2010 from 1995levels are discussed in the TAR (IPCC, 2001a). US EPA (2006a) reports that emission levels from semiconductor manufacture were about 30 MtCO2-eq (7 MtC-eq) in 2000, and that significant growth in emissions will occur unless the WSC commitment is implemented globally and strengthened after 2010. US EPA (2006a) estimates that this 10% reduction could occur cost-effectively through replacement of C2F6 by C3F8 (which has a lower GWP), NF3 remote cleaning of the chemical vapour deposition chamber, or capturing and recycling of SF6. Emissions from the production of liquid crystal displays and photovoltaic cells, mainly located in Asia, Europe and the USA, are growing rapidly and mitigation options need further research. SF6 emissions in 2000 from the production of medium and high voltage electrical transmission and distribution equipment were estimated at about 10 MtCO2-eq (2.8 MtC-eq) (IEA GHG, 2001). These emissions, mainly located in Europe and Japan, are estimated to have declined, despite a 60% growth in production between 1995 and 2003, mainly due to targeted training of staff and improved gas handling and test procedures at production sites. Emissions of SF6 at the end-of-life of electrical equipment are growing in relevance, and US EPA (2006b) estimates total SF6 emissions from production, use and disposal of electrical equipment at 27 MtCO2 in 2000 growing to 66 MtCO2 in 2020, if no mitigation actions are taken. Emissions from disposal of electrical equipment could be reduced by implementation of a comprehensive recovery system, addressing all entities involved in handling and dismantling this equipment (Wartmann and Harnisch, 2005). A third group of industries that emits hydrofluorocarbons (HFCs) includes those manufacturing rigid foams, refrigeration and air conditioning equipment and aerosol cans, as well as industries using fluorinated compounds as solvents or for cleaning purposes. This group of industries previously used ozone-depleting substances (ODS), which are subject to declining production and use quotas defined under the Montreal Protocol. As part of the phase out of ODS, many of them have switched to HFCs as replacements, or intend to do so in the future. Mitigation options include improved containment, training of staff, improved recycling at the end-of-life, the use of very low GWP alternatives, and the application of not-in-kind technologies. A detailed discussion of use patterns, emission projections and mitigation options for these applications can be found in IEA GHG (2001), IPCC/TEAP (2005) and more recent US EPA reports (2006a,b). IEA GHG (2001) estimated that global fugitive emissions from the production of HFCs will rise from 2 MtCO2-eq (0.6 MtC-eq) in 1996 to 8 MtCO2-eq (2.2 MtC-eq) by 2010. Solvent and cleaning uses of HFCs and PFCs are commonly emissive despite containment and recycling measures. IEA GHG (2001) 471
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forecast that these emissions would increase to up to 20 MtCO2eq/yr (5.5 MtC-eq/yr) by 2020. However other analyses suggest a more moderate growth in emissions from solvent applications to about 5 MtCO2-eq/yr (1.4 MtC-eq/yr) by 2020 (IPCC/TEAP, 2005).
economic factors (e.g., costs and discount rates). In many cases study assumptions are not specified, making it impossible to adjust the studies to a common basis, or to quantify overall uncertainty. A full discussion of the basis for evaluating costs in this report appears in Chapter 2.5.
7.4.9
Table 7.8 presents an assessment of the industry-specific literature. Mitigation potential and cost for industrial CO2 emissions were estimated as follows: (1) Price et al. (2006)’s estimates for 2030 production rate by industry and geographic area for the SRES A1 and B2 scenarios (IPCC, 2000b) were used. (2) Literature estimates of mitigation potential were used, where available. In other cases, mitigation potential was estimated by assuming that current best practice could be achieved by all plants in 2030. (3) Literature estimates of mitigation cost were used, where available. When literature values were not available, expert judgment (informed by the available literature and data) was used to assign costs to mitigation technology.
Inter-industry options
Some options for reducing GHG emissions involve more than one industry, and may increase energy use in one industry to achieve a greater reduction in energy use in another industry or for the end-use consumer. For example, the use of granulated slag in Portland cement may increase energy use in the steel industry, but can reduce both energy consumption and CO2 emissions during cement production by about 40%. Depending on the concrete application, slag content can be as high as 60% of the cement, replacing an equivalent amount of clinker (Cornish and Kerkhoff, 2004). Lightweight materials (high-tensile steel, aluminium, magnesium, plastics and composites) often require more energy to produce than the heavier materials they replace, but their use in vehicles will reduce transport sector energy use, leading to an overall reduction in global energy consumption. Life-cycle calculations (IAI, 2000) indicate that the CO2 emission reductions in vehicles resulting from the weight reduction achieved by using aluminium more than offsets the GHG emissions from producing the aluminium. Co-siting of industries can achieve GHG mitigation by allowing the use of byproducts as useful input and by integrating energy systems. In Kalundborg (Denmark) various industries (e.g., cement and pharmaceuticals production and a CHP plant) form an eco-industrial park that serves as an example of the integration of energy and material flows (Heeres et al., 2004). Heat-cascading systems, where waste heat from one industry is used by another, are a promising cross-industry option for saving energy. Based on the Second Law of Thermodynamics, Grothcurth et al. (1989) estimated up to 60% theoretical energy saving potential from heat cascading systems. However, Matsuhashi et al. (2000) found the practical potential of these systems was limited to approximately 5% energy saving. Actual potential will depend on site-specific conditions.
7.5 Short- and medium-term mitigation potential and cost Limited information is available on mitigation potential and cost9 in industry, but it is sufficient to develop a global estimate for the industrial sector. Available studies vary widely with respect to system boundaries, baseline, time period, subsectors included, completeness of mitigation measures included, and
9
Cost estimates are reported as 2030 mitigation potential below a given cost level. In most cases it was not possible to develop a marginal abatement cost curve that would allow estimation of mitigation potential as a function of cost. Estimates have not been made for some smaller industries (e.g., glass) and for the food industry. One or more of the critical inputs needed for these estimates were missing. Table 7.8 should be interpreted with care. It is based on a limited number of studies – sometimes only one study per industry – and implicitly assumes that current trends will continue until 2030. Key uncertainties in the projections include: the rate of technology development and diffusion, the cost of future technology, future energy and carbon prices, the level of industrial activity in 2030, and policy driver, both climate and non-climate. The use of two scenarios, A1B and B2, is an attempt to bracket the range of these uncertainties. Table 7.8 projects 2030 mitigation potential for the industrial sector at a cost of <100 US$/tCO2-eq (<370 US$/tC-eq) of 3.0 to 6.3 GtCO2-eq/yr (0.8 to 1.7 GtC-eq/yr) under the A1B scenario, and 2.0 to 5.1 GtCO2-eq/yr (0.6 to 1.4 GtC-eq/yr) under the B2 scenario. The largest mitigation potentials are found in the steel, cement, and pulp and paper industries and in the control of nonCO2 gases. Much of that potential is available at <50 US$/tCO2eq (<180 US$/tC-eq). Application of CCS technology offers a large additional potential, albeit at higher cost (low agreement, little evidence). Some data are available on industrial sector mitigation potential and cost by country or region. However, an attempt
Mitigation potential is the ‘economic potential’, which is defined as the amount of GHG mitigation that is cost-effective for a given carbon price, with energy savings included, when using social discount rates (3-10%).
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to build-up a global estimate from this data was unsuccessful. Information was lacking for the former Soviet Union, Africa, Latin America and parts of Asia. 7.5.1
Electricity savings
Electricity savings are of particular interest, since they feedback into the mitigation potential calculation for the energy sector and because of the potential for double counting of the emissions reductions. Section 7.3.2 indicates that in the EU and USA electric motor driven systems account for about 65% of industrial energy use, and that efficient systems could reduce this use by 30%. About one-third of the savings potential was assumed to be realized in the baseline, resulting in a net mitigation potential of 13% of industrial electricity use. This mitigation potential was included in the estimates of mitigation potential for energy-intensive industries presented in Table 7.8. However, it is also necessary to consider the potential for electricity savings from non-energy-intensive industries, which are large consumers of electricity. The estimation procedure used to develop these numbers was as follows: Because data could not be found on other countries/regions, US data (EIA, 2002) on electricity use as a fraction of total energy use by industry and on the fraction of electricity use consumed by motor driven systems was taken as representative of global patterns. Based on De Keulenaer et al. (2004) and Xenergy (1998), a 30% mitigation potential was assumed. Emission factors to convert electricity savings into CO2 reductions were derived from IEA data (IEA, 2004). The emission reduction potential from non-energy-intensive industries were calculated by subtracting the savings from energy-intensive industries from total industrial emissions reduction potential. Using the B2 baseline, 49% of total electricity savings are found in industries other than those identified in Table 7.8. 7.5.2
Non-CO2 gases
Table 7.9 shows mitigation potential for non-CO2 gases in 2030 based on a global study conducted by the US EPA (2006a,b), which projected emission and mitigation costs to 2020. Emissions in 2030 were projected by linear extrapolation by region using 2010 and 2020 data. Mitigation costs were assumed to be constant between 2020 and 2030, and interpolated from US EPA data, which used different cost categories. The analysis uses US EPA’s technical adoption scenario, which assumes that industry will continue meeting its voluntary commitments. The SRES A1B and B2 scenarios used as the base case for the rest of this chapter do not include sufficient detail on non-CO2 gases to allow a comparison of the two approaches. IPCC/TEAP (2005) contains significantly different estimates of 2015 baseline emissions for HFCs and PFCs in some sectors compared to Table 7.9. We note that these emissions are reported by end-use, not by the sectoral approach
used in this report, and that insufficient information is provided to extrapolate to 2030. Caprolactam projections were not found in the literature. They were estimated based on historical data from a variety of industry sources. Mitigation costs and potentials were estimated by applying costs and potential from nitric acid production. 7.5.3
Summary and comparison with other studies
Using the SRES B2 as a baseline (see Section 11.3.1), Table 7.10 summarizes the mitigation potential for the different cost categories. To avoid double counting, the total mitigation potential as given in Table 7.8 has been corrected for changes in emission factors of the transformation sectors to arrive at the figures included in Table 7.10 (see also Chapter 11, table 11.3). Two recent studies provide bottom-up, global estimates of GHG mitigation potential in the industrial sector in 2030. IEA (2006a) used its Energy Technology Perspectives Model (ETP), which belongs to the MARKAL family of bottom-up modelling tools, to estimate mitigation potential for CO2 from energy use in the industrial sector to be 5.4 Gt/yr (1.5 GtC/yr) in 2050. IEA’s base case was an extrapolation of its World Energy Outlook 2005 Reference Scenario, which projected energy use to 2030. IEA provides ranges for mitigation potential in 2030 for nine groups of technologies totalling about 2.5 to 3.0 GtCO2/yr (0.68 to 0.82 GtC/yr). Mitigation cost is estimated at <25 US$/tCO2 (<92 US$/tC) (2004 US$). While IEA’s estimate of mitigation potential is in the range found in this assessment, their estimate of mitigation cost is significantly lower. ABARE (Matysek et al., 2006) used its general equilibrium model of the world economy (GTEM) to estimate the emission reduction potential associated with widespread adoption of advanced technologies in five key industries: iron and steel, cement, aluminium, pulp and paper, and mining. In the most optimistic ABARE scenario, industrial sector emissions across all gases are reduced by an average of about 1.54 GtCO2-eq/ yr) (0.42GtC-eq/yr) over the 2001 to 2050 time frame and 2.8 GtCO2-eq/yr (0.77 GtC-eq/yr) over the 2030-2050 time frame, relative to the GTEM reference case, which assumes energy efficiency improvements and continuation of current or announced future government policy. The ABARE carbon dioxide only industry mitigation potential for the period 2030– 2050 of approximately 1.94 GtCO2-eq/yr (0.53GtC/yr) falls below the range developed in this assessment. This outcome is the likely result of differences in the modelling approaches used – ABARE’s GTEM model is a top down model whereas the mitigation potentials in this assessment are developed using detailed bottom-up methodologies. ABARE did not estimate the cost of these reductions. The TAR (IPCC, 2001a) developed a bottom up estimate of mitigation potential in 2020 for the industrial sector of 1.4 to 1.6 GtC (5.1 to 5.9 GtCO2) based an SRES B2 scenario baseline
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Table 7.8: Mitigation potential and cost in 2030 2030 production (Mt)a Product
Areab
A1
B2
GHG intensity (tCO2-eq/t prod.)
Mitigation potential (%)
Cost range (US$)
Mitigation potential (MtCO2-eq/yr) A1
B2
CO2 emissions from processes and energy use Steelc,d
Global
1,163
1,121
1.6-3.8
15-40
20-50
430-1,500
420-1,500
OECD
370
326
1.6-2.0
15-40
20-50
90-300
80-260
EIT
162
173
20.-3.8
25-40
20-50
80-240
85-260
Dev. Nat.
639
623
1.6-3.8
25-40
20-50
260-970
250-940
8.4
15-25
<100
53-82
49-75
Primary
Global
39
37
aluminiume,f
OECD
12
11
8.5
15-25
<100
16-25
15-22
9
6
8.6
15-25
<100
12-19
8-13
19
20
8.3
15-25
<100
25-38
26-40
Global
6,517
5,251
0.73-0.99
11-40
<50
720-2,100
480-1,700
OECD
600
555
0.73-0.99
11-40
<50
65-180
50-160
EIT Dev. Nat. Cementg,h,i
EIT
362
181
0.81-0.89
11-40
<50
40-120
20-60
5,555
4,515
0.82-0.93
11-40
<50
610-1,800
410-1,500
Global
329
218
1.33
20
<20
85
58
OECD
139
148
1.33
20
<20
35
40
19
11
1.33
20
<20
5
3
Dev. Nat.
170
59
1.33
20
<20
45
15
Global
218
202
1.6-2.7
25
<20
110
100
OECD
23
20
1.6-2.7
25
<20
11
10
EIT
21
23
1.6-2.7
25
<20
10
12
Dev. Nat. Ethylenej
EIT
Ammoniak,l
175
159
Petroleum
Dev. Nat. Global
4,691
4,508
refiningm
OECD
2,198
2,095
384
381
Dev. Nat.
2,108
2,031
0.32-0.64
Global
1,321
920
0.22-1.40
5-40
<20
49-420
37-300
OECD
695
551
0.22-1.40
5-40
<20
28-220
22-180
65
39
0.22-1.40
5-40
<20
3-21
2-13
561
330
0.22-1.40
5-40
<20
18-180
13-110
EIT
Pulp and papern
EIT Dev. Nat.
1.6-2.7
25
<20
87
80
0.32-0.64
10-20
Half <20
150-300
140-280
0.32-0.64
10-20
Half <50
70-140
67-130
0.32-0.64
10-20
“
12-24
12-24
10-20
“
68-140
65-130
Notes and sources: a Price et al., 2006. b Global total may not equal sum of regions due to independent rounding. c Kim and Worrell, 2002a. d Expert judgement. e Emission intensity based on IAI Life-Cycle Analysis (IAI, 2003), excluding alumina production and aluminium shaping and rolling. Emissions include anode manufacture, anode oxidation and power and fuel used in the primary smelter. PFC emission included under non-CO2 gases. f Assumes upgrade to current state-of-the art smelter electricity use and 50% penetration of zero emission inert electrode technology by 2030. g Humphreys and Mahasenan, 2002. h Hendriks et al., 1999. i Worrell et al., 1995. j Ren et al., 2005. k Basis for estimate: 10 GJ/t NH difference between the average plant and the 3 best available technology (Figure 7.2) and operation on natural gas (Section 7.4.3.2). l Rafiqul et al., 2005. m Worrell and Galitsky, 2005. n Farahani et al., 2004. o The process emissions from ammonia manufacturing (based on natural gas) are about 1.35 tCO2/t NH3 (De Beer, 1998). However, as noted in Section
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7.4.3.2, the fertilizer industry uses nearly half of the CO2 it generates for the production of urea and nitrophosphates. The remaining CO2 is suitable for storage. IPCC (2005a) indicates that it should be possible to store essentially all of this remaining CO2 at a cost of <20 US$/t. p IPCC, 2005a. q US refineries use about 4% of their energy input to manufacture hydrogen (Worrell and Galitsky, 2005). Refinery hydrogen production is expected to increase as crude slates become heavier and the demand for clean products increases. We assume that in 2030, 5% of refinery energy use worldwide will be used for hydrogen production, and that the byproduct CO2 will be suitable for carbon storage. r Total potential and application potential derived from IEA, 2006a. Subdivision into regions based in production volumes and carbon intensities. IEA, 2006a does not provide a regional breakdown. s Extrapolated from US EPA, 2006b. This publication does not use the SRES scenarios as baselines. t See Section 7.5.1 for details of the estimation procedure. u Due to gaps in quantitative information (see the text) the column sums in this table do not represent total industry emissions or mitigation potential. Global total may not equal sum of regions due to independent rounding. v The mitigation potential of the main industries include electricity savings. To prevent double counting with the energy supply sector, these are shown separately in Chapter 11. w Mitigation potential for other industries includes only reductions for reduced electricity use for motors. Limited data in the literature did not allow estimation of the potential for other mitigation options in these industries.
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Industry
Table 7.8: Continued 2030 production (Mt)a Product
Areab
A1
B2
CCS Potential (tCO2/t)
218
202
0.5
Mitigation potential (%)
Cost range (US$)
about 100
<50
Mitigation potential (MtCO2-eq) A1
B2
150
140
Carbon Capture and Storage Ammoniao,p
Global OECD
23
20
0.5
about 100
<50
15
13
EIT
21
23
0.5
about 100
<50
14
16
175
159
0.5
about 100
<50
120
110
Dev. Nat. Petroleum
Global
4,691
4,508
0.032-0.064
about 50
<50
75-150
72-150
Refiningm,p,q
OECD
2,198
2,095
0.032-0.064
about 50
<50
35-70
34-70
EIT
Cementr
Iron and Steel
384
381
0.032-0.064
about 50
<50
6-12
6-12
Dev. Nat.
2,108
2,031
0.032-0.064
about 50
<50
34-70
32-65
Global
6,517
5,251
0.65-0.89
about 6
<100
250-350
200-280
OECD
600
555
0.65-0.80
about 6
<100
23-32
22-27
EIT
362
181
0.73-0.80
about 6
<100
16-17
8-9
Dev. Nat.
5,555
4,515
0.74-0.84
about 6
<100
210-300
170-240
Global
1,163
1,121
0.32-0.76
about 20
<50
70-180
70-170
OECD
370
326
0.32-0.40
about 20
<50
24-30
21-26
EIT
162
173
0.40-0.76
about 20
<50
13-25
14-26
Dev. Nat.
639
623
0.32-0.76
about 20
<50
33-120
35-120
Non-CO2 gasesr Global
668
37% <0US$
380
OECD
305
53% <20US$
160
53
55% <50US$
29
310
57%<100US$
190
EIT Dev. Nat. Other industries, electricity conservations Global
25% <20
1,100-1,300
410-540
OECD
25% <50
140-210
65-140
EIT
50% <100
340-350
71-85
d
640-700
280-320
Global
3,000-6,300
2,000-5,100
OECD
580-1,300
470-1,100
Dev. Nat. Sumt,u,v,w
EIT Dev. Nat.
and on the evaluation of specific technologies. Extrapolating the TAR estimate to 2030 would give values above the upper end of the range developed in this assessment. The newer studies used in this assessment take industry-specific conditions into account, which reduces the risk of double counting.
7.6 Barriers to industrial GHG mitigation Full use of mitigation options is not being made in either industrialized or developing nations (high agreement, much
540-830
250-510
2,000-4,300
1,300-3,400
evidence). In many areas of the world, GHG mitigation is neither demanded nor rewarded by the market or government. In these areas, companies will invest in GHG mitigation to the extent that other factors provide a return for their investments. This return can be economic, for example energy-efficiency improvements that show an economic payout. Nicholson (2004) reported that the projects BP undertook to lower its CO2 emissions by 10% increased shareholder value by US$ 650 million. Alternatively, the return can be in terms of achievement of a larger corporate goal, for example DuPont’s commitment to cut its GHG emission by two-thirds as part of a larger commitment to sustainable growth (Holliday, 2001). 475
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Table 7.9: Global mitigation potential in 2030 for non-CO2 gases 2030 Baseline emissions (MtCO2-eq)
Source N2O from adipic and nitric acid production
20
PFC from aluminium production
51
PFC and SF6 from semiconductor manufacture
20
SF6 from use of electrical equipment (excluding manufacture)
74
SF6 from magnesium production HFC-23 from HCFC-22 production ODSa
substitutes: aerosols
<20
<50
158
158
158
174
16
16
16
16
1.6 9.6 32 9.2
7.6 9.6 39 9.2
8.2
<100
8.2
10
10
39
39
9.2
9.2
106
0
86
86
86
88
27
27
27
27
80
3.5
3.5
3.5
3.5
ODS substitutes: fire extinguishing
27
0
0
6.3
6.7
Total:
4.0
1.2
2.0
2.0
2.0
Global
668
249
357
364
380
OECDb
305
135
154
157
158
Economies in Transition Developing Nations b
9.3
<0
ODS substitutes: industrial refrigeration and cooling
ODS substitutes: solvents
a
190
N2O from caprolactam production
Mitigation potential by cost category (US$)
53
27
28
29
29
309
87
182
187
187
ODS = Ozone-Depleting Substances Regional information given in references.
Source: Extrapolated from US EPA 2006a,b.
Even though a broad range of cost-effective GHG mitigation technologies exist, a variety of economic barriers prevent their full realisation in both developed and developing countries. Policies and measures must overcome the effective costs of capital (Toman, 2003). Industry needs a stable, transparent policy regime addressing both economic and environmental concerns to reduce the costs of capital. The slow rate of capital stock turnover in many of the industries covered in this chapter is a barrier to mitigation (Worrell and Biermans, 2005). Excess capacity, as exists in some industries, can further slow capital stock turnover. Policies that encourage capital stock turnover, such as Japan’s programme to subsidize the installation of new high performance furnaces (WEC, 2001), will increase GHG mitigation. Companies must also take into consideration the risks involved with adopting a new technology, the payback period of a technology, the appropriate discount rate and transaction costs. Newer, relatively expensive technologies often have longer payback periods and represent a greater risk. Reliability is a key concern of industry, making new technologies less attractive (Rosenberg, 1999). Discount rates vary substantially across industries and little information exists on transaction costs of mitigation options (US EPA, 2003). Resource constraints are also a significant barrier to mitigation. Unless legally mandated, GHG mitigation will have to compete for financial and technical resources against projects to achieve other company goals. Financial constraints can hinder 476
diffusion of technologies within firms (Canepa and Stoneman, 2004). Projects to increase capacity or bring new products to the market typically have priority, especially in developing countries, where markets are growing rapidly and where a large portion of industrial capacity is in SMEs. Energy efficiency and other GHG mitigation technologies can provide attractive rates of return, but they tend to increase initial capital costs, which can be a barrier in locations where capital is limited. If the technology involved is new to the market in question, even if it is well-demonstrated elsewhere, the problem of raising capital may be further exacerbated (Shashank, 2004). Provision of funding for demonstration of the technology can overcome this barrier (CPCB, 2005). The rate of technology transfer is another factor limiting the adoption of mitigation technologies. As documented in the IPCC Special Report Methodological and Technological Issues in Technology Transfer (IPCC, 2000c), lack of an enabling environment is a barrier to technology transfer in some countries. Even when an enabling environment is present, the ability of industrial organizations to access and absorb information on technologies is limited. Access to information tends to be more of a problem in developing nations, but all companies, even the largest, have limited technical resources to interpret and translate the available information. The success of programmes such as US DOE’s Industrial Technologies Programs (ITP) and of the voluntary information sharing programmes discussed in Section 7.9.2 is evidence of the pervasiveness of this barrier.
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Table 7.10: Estimated economic potentials for GHG mitigation in industry in 2030 for different cost categories using the SRES B2 baseline Economic potential <100 US$/tCO2-eq Mitigation option
Region
Economic potential in different cost categories
Cost category (US$/tCO2-eq)
<0
0-20
20-50
50-100
Cost category (US$/tC-eq)
<0
0-73
73-183
183-367
Low
High
(MtCO2-eq) OECD Electricity savings
70
70
150
80
20
20
40
100
100
250
300
250
50
EIT Non-OECD/EIT OECD
Other savings, including non-CO2 GHG
300
EIT Non-OECD/EIT OECD EIT
450 350
900
200
450
80
250
20
1,200
3,300
500
1,700
80
600
1,200
350
350
200
250
550
100
250
60
Non-OECD/EIT
1,600
3,800
600
1,800
300
Global
2,500
5,500
1,100
2,400
550
Total
McKane et al. (2005) provide a case study of the interaction of some of these elements in their analysis of the barriers to the adoption of energy-efficient electric motors and motor-systems. These include: (1) industrial markets that focus on components, not systems; (2) energy efficiency not being a core mission for most industries, which results in a lack of internal support systems for mitigation goals; and (3) lack of technical skills to optimize the systems to the specific application – one size does not fit all. They found industrial energy efficiency standards a useful tool in overcoming these barriers.
7.7 Sustainable Development (SD) implications of industrial GHG mitigation Although there is no universally accepted, practical definition of SD, the concept has evolved as the integration of economic, social and environmental aims (IPCC, 2000a; Munasinghe, 2002). Companies worldwide adopted Triple Bottom Line (financial, environmental and social responsibility) reporting in the late 1990’s. The Global Reporting Initiative (GRI, n.d.), a multi-stakeholder process, has enabled business organizations to account for and better explain their contributions to sustainable development. Companies are also reporting under Sigma Guidelines (The Sigma Project, 2003a), and AA1000 (The Sigma Project, 2003b) and SA 8000 (SAI, 2001) procedures. Many companies are trying to demonstrate that their operations minimize water use and carbon emissions and produce zero solid waste (ITC, 2006). SD consequences can be observed or monitored through various indicators grouped under the three
major categories. (See Section 12.1.1 and 12.1.3 for more detail). However, the SD consequences of mitigation options are not automatic. GHG mitigation, per se, has little impact on four of the SD indicators: poverty reduction, empowerment/gender, water pollution and solid waste. The literature indicates that supplementing mitigation options with appropriate national macroeconomic policies, and with social and local waste reduction strategies at the company level (Tata Steel, Ltd., 2005; BEE, 2006), has achieved some sustainability goals. Economywide impact studies (Sathaye et al., 2005; Phadke et al., 2005) show that in developing countries, like India, adoption of efficient electricity technology can lead to higher employment and income generation. However, the lack of empirical studies leads to much uncertainty about the SD implications of many mitigation strategies, including use of renewables, fuel switching, feedstock and product changes, control of nonCO2 gases, and CCS. For example, fuel switching can have a positive effect on local air pollution and company profitability, but its impacts on employment are uncertain and will depend on inter-input substitution opportunities. GHG emissions mitigation policies induce increased innovation that can reduce the energy and capital intensity of industry. However, this could come at the expense of other, even more valuable, productivity-enhancing investments or learning-by-doing efforts (Goulder and Schneider, 1999). If policies are successful in stimulating economic activity, they are also likely to stimulate increased energy use. GHG emissions would increase unless policies decreased the carbon-intensity of economic activity by more than the increase in activity. 477
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Due to energy efficiency improvements and fuel switching in OECD countries (Schipper et al., 2000; Liskas et al., 2000), as well as in developing countries like India (Dasgupta and Roy, 2001), China (Zhang, 2003), Korea (Choi and Ang, 2001; Chang, 2003), Bangladesh (Bain, 2005), and Mexico (Aguayo and Gallagher, 2005), energy and carbon intensity have decreased, for the industry sector in general and for energyintensive industries in particular. In Mexico, deindustrialization also played a role. For OECD countries, structural change has also played an important role in emissions reduction. However, overall economic activity has increased more rapidly, resulting in higher total carbon emissions. SMEs have played a part in advancing the SD agenda, for example as part of coordinated supply chain or industrial park initiatives, or by participating in research and innovation in sustainable goods and services (Dutta et al., 2004). US DOE’s Industrial Assessment Centers (IACs) are an example of how SMEs can be provided with financial and technical support to assess and identify energy and cost-saving opportunities and training to improve human capital (US DOE, 2003).
7.8 Interaction of mitigation technologies with vulnerability and adaptation Industry’s vulnerability to extreme weather events arises from site characteristics, for example coastal areas or floodprone river basins (high agreement, much evidence). Because of their financial and technical resources, large industrial organizations typically have a significant adaptive capacity for addressing vulnerability to weather extremes. SMEs typically have fewer financial and technical resources and therefore less adaptive capacity. The food processing industry, which relies on agricultural resources that are vulnerable to extreme weather conditions like floods or droughts, is engaging in dialogue with its supply chain to reduce GHGs emissions. Companies are also attempting to reduce vulnerability through product diversification (Kolk and Pinkse, 2005). Linkages between adaptation and mitigation in the industrial sector are limited. In areas dependent on hydropower, mitigation options that reduce industrial electricity demand will help in adapting to climate variability or change that affects water supply (Subak et al., 2000). Many mitigation options (e.g., energy efficiency, heat and power recovery, recycling) are not vulnerable to climate change and therefore create no additional adaptation link. Others, such as fuel switching can be vulnerable to climate change under certain circumstances. As the 2005 Atlantic hurricane season demonstrated, the oil and gas infrastructure is vulnerable to weather extremes. Use of solar or biomass energy will be vulnerable to both weather extremes and climate change. Adaptation, the construction of more weather resistant facilities and provision of back-up energy supplies could reduce this vulnerability. 478
Chapter 7
7.9 Effectiveness of and experience with policies As noted in the TAR (IPCC, 2001b), industrial enterprises of all sizes are vulnerable to changes in government policy and consumer preferences. While the specifics of government climate policies will vary greatly, all will have one of two fundamental objectives: constraining GHG emissions or adapting to existing or projected climate change. And while consumers may become more sensitive to the GHG impacts of the products and services they use, it is almost certain that they will continue to seek the traditional qualities of low-cost, reliability, etc. The challenge to industry will be to continue to provide the goods and services on which society depends in a GHG-constrained world. Industry can respond to the potential for increased government regulation or changes in consumer preferences in two ways: by mitigating its own GHG emissions or by developing new, lower GHG emission products and services. To the extent that industry does this before required by either regulation or the market, it is demonstrating the type of anticipatory, or planned, adaptation advocated in the TAR (IPCC, 2001b). 7.9.1
Kyoto mechanisms (CDM and JI)
The Clean Development Mechanism (CDM) was created under the Kyoto Protocol to allow Annex I countries to obtain GHG emission reduction credits for projects that reduced GHG emission in non-Annex I countries, provided that those projects contributed to the sustainable development of the host country (UNFCCC, 1997). As of November 2006, over 400 projects had been registered, with another 900 in some phase of the approval process. Total emission reduction potential of both approved and proposed projects is nearly 1.5 GtCO2 (410 MtC). The majority of these projects are in the energy sector; as of November 2006, only about 6% of approved CDM projects were in the industrial sector (UNFCCC, CDM, n.d.). The concept of Joint Implementation (JI), GHG-emissions reduction projects carried out jointly by Annex I countries or business from Annex I countries, is mentioned in the UNFCCC, but amplified in the Kyoto Protocol. However, since the Kyoto Protocol does not allow JI credits to be transferred before 2008, progress on JI implementation has been slow. Both CDM and JI build on experience gained in the pilot-phase Activities Implemented Jointly (AIJ) programme created by the UNFCCC in 1995 (UNFCCC, 1995). A fuller discussion of CDM, JI and AIJ appears in Section 13.3.3. 7.9.1.1
Regional differences
Project-based mechanisms are still in their early stages of implementation, but significant differences have emerged in the ability of developing countries to take advantage of them. This is particularly true of Africa, which, as of November 2006, lagged behind other regions in their implementation. Only two
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Industry
of fifty AIJ projects were in Africa. None of the twenty projects recently approved under The Netherlands carbon purchase programme, CERUPT, were in Africa (CDM for Sustainable Africa, 2004), and only 3% of the registered CDM projects were in Africa (UNFCCC, CDM, n.d.). Yamba and Matsika (2004) identified financial, policy, technical and legal barriers inhibiting participation in the CDM in sub-Saharan Africa. Financial barriers pose the greatest challenges: low market value of carbon credits, high CDM transaction costs and lack of financial resources discourage industry participation. Policy barriers include limited awareness of the benefits of CDM and the project approval process in government and the private sector, non-ratification of the Kyoto Protocol, and failure to establish the Designated National Authorities required by CDM. Technical barriers include limited awareness of the availability of energy-saving and other appropriate technologies for potential CDM projects. Legal barriers include limited awareness in government and the private sector of the Kyoto Protocol, and the legal requirements for development of CDM projects. Limited human resources for the development of CDM projects, and CDM’s requirements on additionality are additional constraints. Other countries, for example Brazil, China and India (Silayan, 2005), have more capacity for the development of CDM projects. The Government of India (GOI, 2004) has identified energy efficiency in the steel industry as one of the priorities for Indian CDM projects. 7.9.2 7.9.2.1
Voluntary GHG programmes and agreements Government-initiated GHG programmes and voluntary agreements
Government-initiated GHG programmes and agreements that focus on energy-efficiency improvement, reduction of energy-related GHG emissions and reduction of non-CO2 GHG emissions are found in many countries. Voluntary Agreements are defined as formal agreements that are essentially contracts between government and industry that include negotiated targets with time schedules and commitments on the part of all participating parties (IEA, 1997). Voluntary agreements for energy efficiency improvement and reduction of energyrelated GHG emissions by industry have been implemented in industrialized countries since the early 1990s. These agreements fall into three categories: completely voluntary; voluntary with the threat of future taxes or regulation if shown to be ineffective; and voluntary, but associated with an energy or carbon tax (Price, 2005). Agreements that include explicit targets, and exert pressure on industry to meet those targets, are the most effective (UNFCCC, 2002). An essential part of voluntary agreements is government support, including the programme elements such as information-sharing, energy and GHG emissions management, financial assistance, awards and recognition, standards and target-setting (APERC, 2003; CLASP, 2005; Galitsky et al., 2004; WEC, 2004). Voluntary agreements typically cover a period of five to ten years, so that
strategic energy-efficiency investments can be planned and implemented. There are also voluntary agreements covering process emissions in Australia, Bahrain, Brazil, Canada, France, Germany, Japan, the Netherlands, New Zealand, Norway, the UK and the USA (Bartos, 2001; EFCTC, 2000; US EPA, 1999). Independent assessments find that experience with voluntary agreements has been mixed, with some of the earlier programmes, such as the French Voluntary Agreements on CO2 Reductions and Finland’s Action Programme for Industrial Energy Conservation, appearing to have been poorly designed, failing to meet targets, or only achieving business-as-usual savings (Bossoken, 1999; Chidiak, 2000; Chidiak, 2002; Hansen and Larsen, 1999; OECD, 2002; Starzer, 2000). Recently, a number of voluntary agreement programmes have been modified and strengthened, while additional countries, including some newly industrialized and developing countries, are adopting such agreements in efforts to increase the efficiency of their industrial sectors (Price, 2005). Such strengthened programmes include the French Association des Enterprises por la Réduction de l’Effet de Serre (AERES) agreements, Finland’s Agreement on the Promotion of Energy Conservation in Industry, and the German Agreement on Climate Protection (AERES, 2005; IEA, 2004; RWI, 2004). The more successful programmes are typically those that have either an implicit threat of future taxes or regulations, or those that work in conjunction with an energy or carbon tax, such as the Dutch Long-Term Agreements, the Danish Agreement on Industrial Energy Efficiency and the UK Climate Change Agreements (see Box 13.2). Such programmes can provide energy savings beyond business-asusual (Bjørner and Jensen, 2002; Future Energy Solutions, 2004; Future Energy Solutions, 2005) and are cost-effective (Phylipsen and Blok, 2002). The Long-Term Agreements, for example, stimulated between 27% and 44% (17 to 28 PJ/yr) of the observed energy savings, which was a 50% increase over historical autonomous energy efficiency rates in the Netherlands prior to the agreements (Kerssemeeckers, 2002; Rietbergen et al., 2002). The UK Climate Change Agreements saved 3.5 to 9.8 MtCO2 (1.0 to 2.7 MtC) over the baseline during the first target period (2000–2002) and 5.1 to 8.9 MtCO2 (1.4 to 2.4 MtC) during the second target period (2002–2004) depending upon whether the adjusted steel sector target is accounted for (Future Energy Solutions, 2005). In addition to the energy and carbon savings, these agreements have important longer-term impacts (Delmas and Terlaak, 2000; Dowd et al., 2001) including: • Changing attitudes towards and awareness of energy efficiency; • Reducing barriers to innovation and technology adoption; • Creating market transformations to establish greater potential for sustainable energy-efficiency investments; • Promoting positive dynamic interactions between different actors involved in technology research and development, deployment, and market development, and 479
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• Facilitating cooperative arrangements that provide learning mechanisms within an industry. The most effective agreements are those that set realistic targets, include sufficient government support, often as part of a larger environmental policy package, and include a real threat of increased government regulation or energy/GHG taxes if targets are not achieved (Bjørner and Jensen, 2002; Price, 2005) (medium agreement, much evidence). 7.9.2.2
Company or industry-initiated voluntary actions
Many companies participate in GHG emissions reporting programmes as well as take voluntary actions to reduce energy use or GHG emissions through individual corporate programmes, non-governmental organization (NGO) programmes and industry association initiatives. Some of these companies report their GHG emission in annual environmental or sustainable development reports, or in their Corporate Annual Report. Beginning in the late 1990s, a number of individual companies initiated in-house energy or GHG emissions management programmes and made GHG emissions reduction commitments (Margolick and Russell, 2001; PCA, 2002). Questions have been raised as to whether such initiatives, which operate outside regulatory or legal frameworks, often without standardized monitoring and reporting procedures, just delay the implementation of government-initiated programmes without delivering real emissions reductions (OECD, 2002). Early programmes appear to have produced little benefit. For example, an evaluation of the Germany industry’s self-defined global-warming declaration found that achievements in the first reporting period appeared to be equivalent to business-as-usual trends (Jochem and Eichhammer, 1999; Ramesohl and Kristof, 2001). However, more recent efforts appear to have yielded positive results (RWI, 2004). Examples of targets and the actual reductions achieved include: • DuPont’s reduction of GHG emissions by over 72% while holding energy use constant, surpassing its pledge to reduce GHG emissions by 65% by 2010 and hold energy use constant compared to a 1990 baseline (DuPont, 2002; McFarland, 2005); • BP’s target to reduce GHG emissions by 10% in 2010 compared to a 1990 baseline which was reached in 2001 (BP, 2003; BP, 2005), and • United Technologies Corporation’s goal to reduce energy and water consumption by 25% as a percentage of sales by the year 2007 using a 1997 baseline that was exceeded by achieving a 27% energy reduction and 34% water use reduction through 2002 (Rainey and Patilis, 2000; UTC, 2003). Often these corporate commitments are formalized through GHG reporting programmes or registries such as the World Economic Forum Greenhouse Gas Register where 13 multinational companies disclose the amount of GHGs their
480
worldwide operations produce (WEF, 2005) and through NGO programmes such as the Pew Center on Global Climate Change’s Business Environmental Leadership Council (Pew Center on Global Climate Change, 2005), the World Wildlife Fund’s Climate Savers Program (WWF, n.d.), as well as programmes of the Chicago Climate Exchange (CCX, 2005). Industrial trade associations provide another platform for organizing and implementing GHG mitigation programmes: • The International Aluminium Institute initiated the Aluminium for Future Generations sustainability programme in 2003, which established nine sustainable development voluntary objectives (increased to 12 in 2006), 22 performance indicators, and a programme to provide technical services to member companies (IAI, 2004). Performance to date against GHG mitigation objectives was discussed in Section 7.4.2.1. • The World Semiconductor Council (WSC), comprised of semiconductor industry associations of the United States, Japan, Europe, Republic of Korea and Chinese Taipei, established a target of reducing PFC emissions by at least 10% below the 1995 baseline level by 2010 (Bartos, 2001). • The World Business Council for Sustainable Development (WBCSD) started the Cement Sustainability Initiative in 1999 with ten large cement companies and it has now grown to 16 (WBCSD, 2005). The Initiative conducts research related to actions that can be undertaken by cement companies to reduce GHG emissions (Battelle Institute/WBCSD, 2002) and outlines specific member company actions (WBCSD, 2002). As of 2004, 94% of the 619 kilns of CSI member companies had developed CO2 inventories and three had established emissions reduction targets (WBCSD, 2005). • By 2003, the Japanese chemical industry had reduced its CO2 emissions intensity by 9% compared with 1990-levels (Nippon Keidanren, 2004), but due to increased production, overall CO2 emissions were up by 10.5%. • The European Chemical Industry Council established a Voluntary Energy Efficiency Programme (VEEP) with a commitment to improve energy efficiency by 20% between 1990 and 2005, provided that no additional energy taxes are introduced (CEFIC, 2002). In 2003, the members of the International Iron and Steel Institute, representing 38% of global steel production, committed to voluntary reductions in energy and GHG emission intensities. In most countries this programme is too new to provide meaningful results (IISI, 2006). However, as part of a larger voluntary programme in Japan, Japanese steelmakers committed to a voluntary action programme to mitigate climate change with the goal of a 10% reduction in energy consumption in 2010 against 1990. In fiscal year 2003, this programme resulted in a 6.4% reduction in CO2 intensity emissions against 1990, through improvement of blast furnaces, upgrade of oxygen production plants, installation of regenerative burners and other steps (Nippon Keidanren, 2004).
Chapter 7
7.9.3
Industry
Financial instruments: taxes, subsidies and access to capital
To date there is limited experience with taxing industrial GHG emissions. France instituted an eco-tax on a range of activities, including N2O emission from the production of nitric, adipic and glyoxalic acids. The tax rate is modest (37 US$ (2000) per tonne N2O, or 1.5 US$/tCO2-eq (5.5 US$/tC-eq), but it provides a supplementary incentive for emissions reductions. The UK Climate Change Levy applies to industry only and is levied on all non-household use of coal (0.15 UK pence/kWh or 0.003 US$/kWh), gas (0.15 UK pence/kWh), electricity (0.43 UK pence/kWh or 0.0085 US$/kWh) and non-transport LPG (0.07 UK pence/kWh or 0.0014 US$/kWh). Industry includes agriculture and the public sector. Fuels used for electricity generation or non-energy uses, waste-derived fuels, renewable energy, including quality CHP, which uses specified fuels and meets minimum efficiency standards, are exempt from the tax. The UK Government also provided an 80% discount from the levy for those energy-intensive sectors that agreed to challenging targets for improving their energy efficiency. Climate change agreements have now been concluded with almost all eligible sectors (UK DEFRA, 2006). In 1999, Germany introduced an eco-tax on the consumption of electricity, gasoline, fuel oil and natural gas. Revenues are recycled to subsidize the public pension system. The tax rate for electricity consumed by industrial consumers is € 0.012/ kWh. Very large consumers are exempt to maintain their competitiveness. The impact of this eco-tax on CO2 emissions is still under discussion (Green Budget Germany, 2004). Tax reductions are frequently used to stimulate energy savings in industry. Some examples include: • In the Netherlands, the Energy Investment Deduction (Energie Investeringsaftrek, EIA) stimulates investments in low-energy capital equipment and renewable energy by means of tax deductions (deduction of the fiscal profit of 55% of the investment) (IEA, 2005). • In France, investments in energy efficiency are stimulated through lease credits. In addition to financing equipment, these credits can also finance associated costs such as construction, land and transport (IEA, 2005). • The UK’s Enhanced Capital Allowance Scheme allows businesses to write off the entire cost of energy-savings technologies specified in the ‘Energy Technology List’ during the year they make the investment (HM Revenue & Customs, n.d.). • Australia requires companies receiving more than AU$ 3 million (US$ 2.5 million) of fuel credits to be members of its Greenhouse Challenge Plus programme (Australian Greenhouse Office, n.d.). • Under Singapore’s Income Tax Act, companies that invest in qualifying energy-efficient equipment can write-off the capital expenditure in one year instead of three. (NEEC, 2005).
• In the Republic of Korea, a 5% income tax credit is available for energy-efficiency investments (UNESCAP, 2000). • Romania has a programme where imported energy-efficient technologies are exempt from customs taxes and the share of company income directed for energy efficiency investments is exempt from income tax (CEEBICNet Market Research, 2004). • In Mexico, the Ministry of Energy has linked its energy efficiency programmes with Energy Service Companies (ESCOs). These are engineering and financing specialised enterprises that provide integrated energy services with a wide range and flexibility of technologies to the industrial and service sectors (NREL, 2006). Subsidies are used to stimulate investment in energy-saving measures by reducing investment cost. Subsidies to the industrial sector include: grants, favourable loans and fiscal incentives, such as reduced taxes on energy-efficient equipments, accelerated depreciation, tax credits and tax deductions. Many developed and developing countries have financial schemes to promote industrial energy savings. A WEC survey (WEC, 2004) showed that 28 countries, most in Europe, provide grants or subsidies for industrial energy efficiency projects. Subsides can be fixed amounts, a percentage of the investment (with a ceiling), or be proportional to the amount of energy saved. In Japan, the New Energy and Technology Development Organization (NEDO) pays up to one-third of the cost of each new high performance furnace. NEDO estimates that the project will save 5% of Japan’s final energy consumption by 2010 (WEC, 2001). The Korean Energy Management Corporation (KEMCO) provides, long-term, low interest loans to certified companies (IEA, 2005). Evaluations show that subsidies for industry may lead to energy savings and corresponding GHG emission reductions and can create a larger market for energy efficient technologies (De Beer et al., 2000b; WEC, 2001). Whether the benefits to society outweigh the cost of these programmes, or whether other instruments would have been more cost-effective, has to be evaluated on a case-by-case basis. A drawback to subsidies is that they are often used by investors who would have made the investment without the incentive. Possible approaches for improving their cost-effectiveness include restricting schemes to specific target groups and/or techniques (selected list of equipment, only innovative technologies, etc.), or using a direct criterion of cost-effectiveness. Investors in developing countries tend to have a weak capital basis. Development and finance institutions therefore often play a critical role in implementing energy efficiency and emission mitigation policies. Their role often goes beyond the provision of project finance and may directly influence technology choice and the direction of innovation (George and Prabhu, 2003). The retreat of national development banks in some developing countries (as a result of both financial liberalisation and financial
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crises in national governments) may hinder the widespread adoption of mitigation technologies because of lack of financial mechanisms to handle the associated risk. 7.9.4
Regional and national GHG emissions trading programmes
Several established or evolving national, regional or sectoral CO2 emissions trading systems exist, for example in the EU, the UK, Norway, Denmark, New South Wales (Australia), Canada and several US States. The International Emissions Trading Association (IETA, 2005) provides an overview of systems. This section focuses on issues relevant to the industrial sector. A more in-depth discussion of emission trading can be found in Section 13.2.1. The results of an assessment of the first two years of the UK scheme (NERA, 2004) show that reduction of non-CO2 GHG emissions from industrial sources provided the least cost options. It also found that the heterogeneity of industrial emitters may require a tiered approach for the participation of small, medium-sized and large emitters, that is in respect to monitoring and verification, and described the impacts of individual industrial emitters gaining dominating market power on allowance prices. In January 2005, the European Union Greenhouse Gas Emission Trading Scheme (EU ETS) was launched as the world’s largest multi-country, multi-sector GHG emission trading scheme (EC, 2005). A number of assessments have analysed current and projected likely future impacts of the EUETS on the industrial sector in the EU (IEA, 2005; Egenhofer et al., 2005). Recurring themes with specific relevance to industry include: allocation approaches based on benchmarking, grandfathering and auctioning; electricity price increases leading to so-called ‘windfall profits’ in the utility sector; competitiveness of energy-intensive industries; specific provisions for new entrants, closures, capacity expansions, and organic growth; and compliance costs for small emitters. The further refinement of these trading systems could be informed by evidence which suggests that in some important aspects participants from industrial sectors face a significantly different situation from those in the electricity sector (Carbon Trust, 2006): • The range of products from industry sectors is generally more diverse (e.g., in the paper, glass or ceramics industry) making it difficult to define sector specific best practice values to be used for the allocation of allowances (see discussion in DTI (2005)). • While grid connections limit electricity to regional or national markets, many industrial products are globally traded commodities, constrained only by transport costs. This increasingly applies as value per mass or volume goes up, that is from bulk ceramics products and cement,
10
IEA’s definition of the industrial sector does not include petroleum refining.
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to petrochemicals, to base metals, making the impacts of trading schemes on international competitiveness a matter of varying concern for the different subsectors. • Only a few industrial sectors (e.g., steel and refineries) are prepared to actively participate in the early phase of trading schemes, leading to reduced liquidity and higher allowance prices, suggesting that specific instruments are needed to increase industrial involvement in trading. • Responses to carbon emission price in industry tend to be slower because of the more limited technology portfolio and absence of short term fuel switching possibilities, making predictable allocation mechanisms and stable price signals a more important issue for industry. The EU Commission recently published its findings and recommendations based on the first year of trading under the EU-ETS (EC, 2006a). An EU High Level Group on Competitiveness, Energy and the Environment has been formed to review the impacts of the EU-ETS on industry (EU-HLG, 2006). Issues highlighted in these EU processes include the need for the allocation of credits to be more harmonized across the EU, the need to increase certainty for investors, that is through long-term clarity on allocations, extension of the scheme to other sectors and alleviation of high participation costs for small installations. Industrial sectors sources considered for inclusion in the EU-ETS include CO2 emissions from ammonia production, N2O emissions from nitric and adipic acid production and PFC emission from aluminium production (EC, 2006b). 7.9.5
Regulation of non-CO2 gases
The first regulations on non-CO2 GHGs are emerging in Europe. A new EU regulation (EC 842/2006) on fluorinated gases includes prohibition of the use of SF6 in magnesium die casting. The regulation contains a review clause that could lead to further use restrictions. National legislation is in place in Austria, Denmark, Luxembourg, Sweden and Switzerland that limits the use of HFCs in refrigeration equipment, foams and solvents. During the review of permits for large emitters under the EU’s Integrated Pollution Prevention and Control (IPPC) Directive (EC, 96/61) a number of facilities have been required to implement best available control technologies for N2O and fluorinated gases (EC, 2006c). 7.9.6
Energy and technology policies
The IEA’s World Energy Outlook 2006 (IEA, 2006c) provides an up-to-date estimate of the impacts of energy policies on the industrial sector10. The IEA compares two scenarios, a Reference Scenario, which assumes continuation of policies currently in place, and an Alternate Policy Scenario, which projects the cumulative impact of the more than 1400 energy
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policies being considered by governments worldwide, many of which affect the industrial sector. The Alternate Policy Scenario assumes faster deployment of commercially demonstrated technology, but not technologies that are still to be commercially demonstrated, including CCS and advanced biofuels. Global industrial energy demand in 2030 in the IEA’s Alternate Policy Scenario is 9% (14 EJ) lower than in the Reference Scenario. Industrial sector CO2 emissions are 12% (0.9 GtCO2) lower. Estimated investment to achieve these savings is US$ 362 billion (2005 US$), US$ 195 billion of which is in electrical equipment. The savings in electricity costs are about three times the investment in electrical equipment. The IEA (2006c) does not provide information on the value of the fuel savings in industry, but clearly it is larger than the investment. Government is expected to lower financial risk and promote the investment through technology policy, which includes diverse options: budget allocations for R&D on innovative technologies, subsidy or legislation to stimulate specific environmental technologies, or regulation to suppress unsustainable technologies. See for example the US DOE’s solicitation for industrial R&D projects (US DOE, n.d.-a) and the Government of India’s Central Pollution Control Board Programmes on development and deployment of energy efficient technologies (CPCB, 2005). 7.9.7
Sustainable Development policies
Appropriate sustainable development policies focusing on energy efficiency, dematerialization and use of renewables can support GHG mitigation objectives. For example, the policy options selected by the Commission on Sustainable Development 13th session to provide a supportive environment for new business formation and the development of small enterprises, included: • Reduce information barriers for energy efficiency technology for industries; • Build capacity for industry associations, and • Stimulate technological innovation and change to reduce dependency on imported fuels, to improve local air pollution and to generate local employment (CSD, 2005). Individual countries are also trying to achieve these objectives. Most policies are stated in general terms, but their implementation would have to include the industrial sector. The EU’s strategy for sustainable development highlights addressing climate change through the reduction of energy use in all sectors and the control of non-CO2 GHGs (EC, 2001). The UK’s sustainable development policy incorporates the UK’s emissions trading and climate levy policies for the control of CO2 emissions from industry (UK DEFRA, 2005). As part of its sustainable development policy, Sweden is emphasizing energy efficiency and a long-term goal of obtaining all energy from
renewable sources (OECD, 2002). China faces a significant challenge in achieving its sustainable development goals, because from 2002 to 2004 its primary energy use grew faster than its GDP, with over two-thirds of that increase coming from coal. In 2005 the Chinese government emphasized that rapid growth must be sustainable and announced the goal of reducing energy consumption per unit of GDP by 20% between 2005 and 2010 (Naughton, 2005). India has launched a series of reforms aimed at achieving industrial sector sustainable development. The 2001 Energy Conservation Act mandated a Bureau of Energy Efficiency charged with ensuring efficient use of energy and use of renewables (GOI, 2004). The Indian Industry Programme for Energy Conservation includes both mandatory and voluntary efforts, with greater emphasis on voluntary approaches (BEE, 2006). These countries are trying to improve resources use efficiency, waste management, water and air pollution reduction, and enhance use of renewables, while providing health benefits and improved services to communities. Many developed (Sutton, 1998) and developing countries (Jindal Steel and Power, Ltd., 2006; ITC, 2006) encourage companies to help achieve these goals thought dematerialization, habitat restoration, recycling, and commitment to corporate social responsibility. 7.9.8
Air quality policies
Section 4.5.2 contains a more general discussion of the relationships between air quality policies and GHG mitigation. In general air quality and climate change are treated as separate issues in national and international policies, even though most practices and technologies that will reduce GHG emissions will also cause a net reduction of emissions of air pollutants. However, air pollutant reduction measures do not always reduce GHG emissions, as many require the use of additional energy (STAPPA/ALAPCO, 1999). Examples of policies dealing with air pollution and GHG emissions in an integrated fashion include: (1) the EU IPPC Directive (96/61/EC), which lays down a framework requiring Member States to issue operating permits for certain industrial installations, and (2) the Dutch plan for a NOx emission trading system, which will be implemented through the same legal and administrational infrastructure as the European CO2 emission trading system (Dekkers, 2003). 7.9.9
Waste management policies
Waste management policies can reduce industrial sector GHG emissions by reducing energy use through the re-use of products (e.g., of refillable bottles) and the use of recycled materials in industrial production processes. Recycled materials significantly reduce the specific energy consumption of the production of paper, glass, steel, aluminium and magnesium. The amount, quality and price of recycled materials are largely determined by waste management policies. These policies can also influence the design of products – including the choice of materials, with its implications for production levels and 483
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Table 7.11: Co-benefits of greenhouse-gas mitigation or energy-efficiency programmes of selected countries Category of Co-benefit
Examples
Health
Reduced medical/hospital visits, reduced lost working days, reduced acute and chronic respiratory symptoms, reduced asthma attacks, increased life expectancy.
Emissions
Reduction of dust, CO, CO2, NOx and SOx; reduced environmental compliance costs.
Waste
Reduced use of primary materials; reduction of waste water, hazardous waste, waste materials; reduced waste disposal costs; use of waste fuels, heat and gas.
Production
Increased yield; improved product quality or purity; improved equipment performance and capacity utilization; reduced process cycle times; increased production reliability; increased customer satisfaction.
Operation and maintenance
Reduced wear on equipment; increased facility reliability; reduced need for engineering controls; lower cooling requirements; lower labour requirements.
Working environment
Improved lighting, temperature control and air quality; reduced noise levels; reduced need for personal protective equipment; increased worker safety.
Other
Decreased liability; improved public image; delayed or reduced capital expenditures; creation of additional space; improved worker morale.
Sources: Aunan et al., 2004; Pye and McKane, 2000; Worrell et al., 2003.
emissions. Prominent examples can be found in the packaging sector, for example the use of cardboard rather than plastic for outer sales packages, or PET instead of conventional materials in the beverage industry. Vertical and horizontal integration of business provides synergies in the use of raw materials and reuse of wastes. The paper and paper boards wastes generated in cigarette packaging and printing are used as raw materials in paper and paper board units (ITC, 2006). Another important influence of waste policies on industrial GHG emissions is their influence on the availability of secondary ‘waste’ fuels and raw materials for industrial use. For example, the ‘EU Landfill Directive’ (EU-OJ, 1999), which limits the maximum organic content of wastes acceptable for landfills, resulted in the restructuring of the European waste sector currently taking place. It makes available substantial amounts of waste containing significant biomass fractions. Typically there is competition between the different uses for these wastes: dedicated incineration in the waste sector, co-combustion in power plants, or combustion in industrial processes, for example cement kilns. In order to provide additional inexpensive disposal routes, several countries have set incentives to promote the use of various wastes in industrial processes in direct competition with dedicated incineration. Emissions trading systems or project-based mechanisms like CDM/JI can provide additional economic incentives to expand the use of secondary fuels or biomass as substitutes for fossil fuels. The impact of switching from a fossil fuel to a secondary fuel on the energy efficiency of the process itself is frequently negative, but is often compensated by energy savings in other parts of the economy. Mineral wastes, such as fly-ash or blast-furnace slag can have several competing alternative uses in the waste, construction and industrial sectors. The production of cement, brick and stone-wool provides energy saving uses for these materials in industry. For secondary fuels and raw materials, life-cycle 484
assessment can help to quantify the net effects of these policies on emission across the affected parts of the economy (Smith et al., 2001). The interactions between climate policies and waste policies can be complex, sometimes leading to unexpected results because of major changes of industry practices and material flows induced by minor price differences.
7.10 Co-benefits of industrial GHG mitigation The TAR explained that ‘co-benefits are the benefits from policy options implemented for various reasons at the same time, acknowledging that most policies resulting in GHG mitigation also have other, often at least equally important, rationales’ (IPCC, 2001a). Significant co-benefits arise from reduction of emissions, especially local air pollutants. These are discussed in Section 11.8.1. Here we focus on co-benefits of industrial GHG mitigation options that arise due to reduced emissions and waste (which in turn reduce environmental compliance and waste disposal costs), increased production and product quality, improved maintenance and operating costs, an improved working environment, and other benefits such as decreased liability, improved public image and worker morale, and delaying or reducing capital expenditures (see Table 7.11) (Pye and McKane, 2000; Worrell et al., 2003). A review of forty-one industrial motor system optimization projects implemented between 1995 and 2001 found that twentytwo resulted in reduced maintenance requirements on the motor systems, fourteen showed improvements in productivity in the form of production increases or better product quality, eight reported lower emissions or reduction in purchases of products such as treatment chemicals, six projects forestalled equipment purchases, and others reported increases in production or decreases in product reject rates (Lung et al., 2003). Motor system
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optimization projects in China are seen as an activity that can reduce operating costs, increase system reliability and contribute to the economic viability of Chinese industrial enterprises faced with increased competition (McKane et al., 2003). A review of 54 emerging energy-efficient technologies, produced or implemented in the USA, EU, Japan and other industrialized countries for the industrial sector, found that 20 of the technologies had environmental benefits in the areas of ‘reduction of wastes’ and ‘emissions of criteria air pollutants’. The use of such environmentally friendly technologies is often most compelling when it enables the expansion of incremental production capacity without requiring additional environmental permits. In addition, 35 of the technologies had productivity or product quality benefits (Martin et al., 2000). Quantification of the co-benefits of industrial technologies is often done on a case-by-case basis. One evaluation identified 52 case studies from projects in the USA, the Netherlands, UK, New Zealand, Canada, Norway and Nigeria that monetized non-energy savings. These case studies had an average simple payback time of 4.2 years based on energy savings alone. Addition of the quantified co-benefits reduced the simple payback time to 1.9 years (Worrell et al., 2003). Inclusion of quantified co-benefits in an energy-conservation supply curve for the US iron and steel industry doubled the potential for costeffective savings (Worrell et al., 2001a; 2003). Not all co-benefits are easily quantifiable in financial terms (e.g., increased safety or employee satisfaction), there are variations in regulatory regimes vis-à-vis specific emissions and the value of their reduction and there is a lack of time series and plant-level data on co-benefits. Also, there is a need to assess net co-benefits, as negative impacts that may be associated with some technologies, such as increased risk, increased training requirements and production losses during technology installation (Worrell et al., 2003).
7.11 Technology Research, Development, Deployment and Diffusion (RDD&D) Most industrial processes use at least 50% more than the theoretical minimum energy requirement determined by the laws of thermodynamics, suggesting a large potential for energy-efficiency improvement and GHG emission mitigation (IEA, 2006a). However, RDD&D is required to capture these potential efficiency gains and achieve significant GHG emission reductions. Studies have demonstrated that new technologies are being developed and entering the market continuously, and that new technologies offer further potential for efficiency improvement and cost reduction (Worrell et al., 2002). While this chapter has tended to discuss technologies only in terms of their GHG emission mitigation potential and cost,
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it is important to realize that successful technologies must also meet a host of other performance criteria, including cost competitiveness, safety, and regulatory requirements; as well as winning consumer acceptance. (These topics are discussed in more detail in Section 7.11.2.) While some technology is marketed as energy-efficient, other benefits may drive the development and diffusion of the technology, as evidenced by a case study of impulse drying in the paper industry, in which the driver was productivity (Luiten and Blok, 2004). This is understandable given that energy cost is just one of the drivers for technology development. Innovation and the technology transfer process are discussed in Section 2.8.2. Technology RDD&D is carried out by both governments (public sector) and companies (private sector). Ideally, the roles of the public and private sectors will be complementary. Flannery (2001) argued that it is appropriate for governments to identify the fundamental barriers to technology and find solutions that improve performance, including environmental, cost and safety performance, and perhaps customer acceptability; but that the private sector should bear the risk and capture the rewards of commercializing technology. Case studies of specific successful energy-efficient technologies, including shoe press in papermaking (Luiten and Blok, 2003a) and strip casting in the steel industry (Luiten and Blok, 2003b), have shown that a better understanding of the technology and the development process is essential in the design of effective government support of technology development. Government can also play an important role in cultivating ‘champions’ for technology development, and by ‘anchoring’ energy and climate as important continuous drivers for technology development (Luiten and Blok, 2003a). While GHG mitigation is not the only objective of energy R&D, IEA studies show a mismatch between R&D spending and the contribution of technologies to reduction of CO2 emissions. In its analysis of its Accelerated Technology scenarios, IEA (2006a) found that end-use energy efficiency, much of it in the industrial sector, contributed most to mitigation of CO2 emissions from energy use. It accounted for 39–53% of the projected reduction, except in the scenario that deemphasized these technologies. However, IEA countries spent only 17% of their public energy R&D budgets on energy-efficiency (IEA, 2005). Many studies have indicated that the technology required to reduce GHG emissions and eventually stabilize their atmospheric concentrations is not currently available (Jacoby, 1998; Hoffert et al., 2002; Edmonds et al., 2003) (medium agreement, medium evidence). While these studies concentrated on energy supply options, they also indicate that significant improvements in end-use energy efficiency will be necessary. Much of the necessary research and development is being carried out in public-private partnerships, for example the US Department of Energy’s Industrial Technologies Program (US DOE, n.d.-b). 485
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7.11.1 Public sector A more complete discussion of public sector policies is presented in Section 7.9 and in Chapter 13. While government use many policies to spur RDD&D in general, this section focuses specifically on programmes aimed at improving energy efficiency and reducing GHG emissions. 7.11.1.1
Domestic policies
Governments are often more willing than companies to fund higher-risk technology research and development. This willingness is articulated in the US Department of Energy’s Industrial Technologies Program role statement: ‘The programme’s primary role is to invest in high-risk, high-value research and development that will reduce industrial energy requirements while stimulating economic productivity and growth’ (US DOE, n.d.-a). The Institute for Environment and Sustainability of the EU’s Joint Research Centre has a similar mission, albeit focusing on renewable energy (Joint Research Centre, n.d.a), as does the programme of the Japanese government’s New Energy and Industrial Technology Development Organization (NEDO, n.d.). Selection of technology is a crucial step in any technology adoption. Governments can play an important role in technology diffusion by disseminating information about new technologies and by providing an environment that encourages the implementation of energy-efficient technologies. For example, energy audit programmes, provide more targeted information than simple advertising. Audits by the US Department of Energy’s Industrial Assessment Center program in SMEs resulted in implementation of about 42% of the suggested measures (Muller and Barnish, 1998). Programmes or policies that promote or require reporting and benchmarking of energy consumption can have a similar function. These programmes have been implemented in many countries, including Canada, Denmark, Germany, the Netherlands, Norway, the UK and the USA (Sun and Williamson, 1999), and in specific industrial sectors such as the petroleum refining, ethylene and aluminium industries. (See Section 7.3.1). Many of the voluntary programmes discussed in Section 7.9.2 include information exchange activities to promote technology diffusion at the national level and across sectors. For 2004, the US Industrial Technologies Program claimed cumulative energy savings of approximately 5 EJ as the result of diffusion of more than 90 technologies across the US industrial sector (US DOE, 2006). EU programmes, for example Lights of the Future and the Motor Challenge Programme (Joint Research Centre, n.d.b), have similar objectives, as do programmes in other regions. A wide array of policies has been used and tested in the industrial sector in industrialized countries, with varying success rates (Galitsky et al., 2004; WEC, 2004). No single 486
instrument will reduce all the barriers to technology diffusion; an integrated policy accounting for the characteristics of technologies, stakeholders and regions addressed is needed. Evenson (2002) suggests that the presence of a domestic research and development programme in a developing country increase the county’s ability to adapt and adopt new technologies. Preliminary analysis seems to suggest that newly industrialized countries are becoming more active in the generation of scientific and technical knowledge, although there is no accurate information on the role of technology development and investments in scientific knowledge in developing countries (Amsden and Mourshed, 1997). 7.11.1.2
Foreign or international policies
Industrial RDD&D programmes assume that technologies are easily adapted across regions with little innovation. This is not always the case. While many industrial facilities in developing nations are new and include the latest technology, as in industrialized countries, many older, inefficient facilities remain. The problem is exacerbated by the presence of large numbers of small-scale, much less energy-efficient plants in some developing nations; for example the iron and steel, cement and pulp and paper industries in China, and in the iron and steel industry in India (IEA, 2006a). This creates a huge demand for technology transfer to developing countries to achieve energy efficiency and emissions reductions. Internationally, there are a growing number of bilateral technology RDD&D programmes to address the slow and potentially sporadic diffusion of technology across borders. A December, 2004 US Department of State Fact Sheet lists 20 bilateral agreements with both developed and developing nations (US Dept. of State, 2004), many of which include RDD&D. Multilaterally, the UNFCCC has resulted in the creation of two technology diffusion efforts, the Climate Technology Initiative (CTI) and the UNFCCC Secretariat’s TT:CLEAR technology transfer database. CTI was established in 1995 by 23 IEA/OECD member countries and the European Commission, and as of 2003 has been recognized as an IEA Implementing Agreement. Its focus is the identification of climate technology needs in developing countries and countries with economiesin-transition, and filling those needs with training, information dissemination and other support activities (CTI, 2005). TT: CLEAR is a more passive technology diffusion mechanism that depends on users accessing the database and finding the information they need (UNFCCC, 2004). Additionally, in 2001, the UNFCCC established an Expert Group on Technology Transfer (EGTT) (UNFCCC, 2001). EGTT has promoted a number of activities including workshops on enabling environments and innovative financing for technology transfer. Ultimately, the Kyoto Protocol’s CDM and JI should act as powerful tools for the diffusion of GHG mitigation technology.
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IEA implementing agreements, for example the Industrial Energy Related Technology and Systems Agreement (IEAIETS, n.d.), also provide a multilateral basis for technology transfer. While still in the planning stage, it is hoped that the newly established Asia-Pacific Partnership on Clean Development and Climate will play a key role in technology transfer to China, India and Korea (APP, n.d.) 7.11.2 Private sector In September, 2004, the IPCC convened an expert meeting on industrial technology development, transfer and diffusion. One of the objectives of the meeting was to identify the key drivers of these processes in the private sector (IPCC, 2005a). Among the key drivers for private sector involvement in the technology process discussed at the meeting were: • Maintaining competitive advantage in open markets; • Consumer acceptance in response to environmental stewardship; • Country-specific characteristics: economic and political as well as its natural resource endowment; • Scale of facilities, which affects the type of technology that can be deployed; • Intellectual property rights (IPR): protection of IPR is critical to achieving competitive advantage through technology. • Regulatory framework, including: government incentives; government policies on GHG emissions reduction, energy security and economic development; rule of law; and investment certainty. The meeting concluded that each of these drivers could either be stimulants or barriers to the technology process, depending on their level, for example a high level of protection for IPR would stimulate the deployment of innovative technology in a specific country while a low level would be a barrier. However, it was also recognized that these drivers were only indicators and that actual decisions had to consider interactions between the drivers, as well as non-technology factors.
7.12 Long-term outlook, system transitions, decision-making and inertia 7.12.1 Longer-term mitigation options Many technologies offer long-term potential for mitigating industrial GHG emissions, but interest has focused in three areas: • Advanced biological processing, in which chemicals are produced by biological reactions that require lower energy input; • Use of hydrogen for metal smelting, in fuel cells for electricity production, and as a fuel – provided the hydrogen is produced via a low or zero-carbon process – and;
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• Nanotechnology, which could provided the basis for more efficient catalysts for chemical processing and for more effective conversion of low-temperature heat into electricity (Hillhouse and Touminen, 2001).
While some applications of these technologies could enter the marketplace by 2030, their widespread application, and impact on GHG emissions, is not expected until post-2030. 7.12.2 System transitions, inertia and decisionmaking Given the complexity of the industrial sector, the changes required to achieve low GHG emissions cannot be characterized in terms of a single system transition. For example, development of an inert electrode for aluminium smelting would significantly lower GHG emissions from this process, but would have no impact on emissions from other industries. Inertia in the industrial sector is characterized by capital stock turnover rate. As discussed in Section 7.6, the capital stock in many industries has lifetimes measured in decades. While opportunities exist for retrofitting some capital stock, basic changes in technology occur only when the capital stock is installed or replaced. This inertia is often referred to as ‘technology lock-in’, a concept first proposed by Arthur (1988). IEA (2006a) discusses the potential effects of technology lockin in electric power generation, where much of the capital stock in developed nations will be replaced, and much of the capital stock in developing nations will be installed, in the next few decades. Installation of lower-cost, but less efficient technology will then impact GHG emission for decades thereafter. The same concerns and impacts apply in the industrial sector. Industrial companies are hierarchical organizations and have well-established decision-making processes. In large companies, these processes have formal methods for incorporating technical and economic information, as well as regulatory requirements, consumer preferences and stakeholder inputs. Procedures in SMEs are often informal, but all successful enterprises have to address the same set of inputs.
7.13 Key uncertainties and gaps in knowledge Gaps in knowledge are defined as missing information that could be developed by research. Uncertainties are missing information that cannot be developed through research. Key uncertainties in the projection of mitigation potential and cost in 2030 are: • The rate of technology development and diffusion; • The cost of future technology; • Future energy and carbon prices; 487
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• The level of industry activity in 2030; and • Policy drivers, both climate and non-climate. Key gaps in knowledge are: base case energy intensity for specific industries, especially in transition economies; cobenefits, SD implications of mitigation options and consumer preferences.
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8 Agriculture Coordinating Lead Authors: Pete Smith (UK), Daniel Martino (Uruguay)
Lead Authors: Zucong Cai (PR China), Daniel Gwary (Nigeria), Henry Janzen (Canada), Pushpam Kumar (India), Bruce McCarl (USA), Stephen Ogle (USA), Frank O’Mara (Ireland), Charles Rice (USA), Bob Scholes (South Africa), Oleg Sirotenko (Russia)
Contributing Authors: Mark Howden (Australia), Tim McAllister (Canada), Genxing Pan (China), Vladimir Romanenkov (Russia), Steven Rose (USA), Uwe Schneider (Germany), Sirintornthep Towprayoon (Thailand), Martin Wattenbach (UK)
Review Editors: Kristin Rypdal (Norway), Mukiri wa Githendu (Kenya)
This chapter should be cited as: Smith, P., D. Martino, Z. Cai, D. Gwary, H. Janzen, P. Kumar, B. McCarl, S. Ogle, F. O’Mara, C. Rice, B. Scholes, O. Sirotenko, 2007: Agriculture. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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Table of Contents Executive Summary .................................................. 499 8.1
Introduction ..................................................... 501
8.2
Status of sector, development trends including production and consumption, and implications............................................... 501
8.3
Emission trends (global and regional) ........ 503
8.3.1
Trends since 1990 ............................................... 503
8.3.2
Future global trends ............................................ 503
8.3.3
8.4
Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability .............. 505
8.4.1
Mitigation technologies and practices ................ 505
8.4.2
Mitigation technologies and practices: per-area estimates of potential .......................................... 511
8.4.3
Global and regional estimates of agricultural GHG mitigation potential ................................... 514
8.4.4
Bioenergy feed stocks from agriculture .............. 519
8.4.5
Potential implications of mitigation options for sustainable development .................................... 520
8.5
498
Regional trends ................................................... 505
Interactions of mitigation options with adaptation and vulnerability ........................ 522
8.6
Effectiveness of, and experience with, climate policies; potentials, barriers and opportunities/implementation issues ......... 522
8.6.1
Impact of climate policies ................................... 522
8.6.2
Barriers and opportunities/implementation issues .................................................................. 525
8.7
Integrated and non-climate policies affecting emissions of GHGs ....................... 525
8.7.1
Other UN conventions......................................... 525
8.7.2
Macroeconomic and sectoral policy ................... 526
8.7.3
Other environmental policies .............................. 526
8.8
Co-benefits and trade-offs of mitigation options ............................................................... 526
8.9
Technology research, development, deployment, diffusion and transfer ............ 530
8.10
Long-term outlook ........................................ 531
References ................................................................... 532
Chapter 8
Agriculture
EXECUTIVE SUMMARY Agricultural lands (lands used for agricultural production, consisting of cropland, managed grassland and permanent crops including agro-forestry and bio-energy crops) occupy about 4050% of the Earth’s land surface. Agriculture accounted for an estimated emission of 5.1 to 6.1 GtCO2-eq/yr in 2005 (10-12% of total global anthropogenic emissions of greenhouse gases (GHGs)). CH4 contributes 3.3 GtCO2-eq/yr and N2O 2.8 GtCO2-eq/yr. Of global anthropogenic emissions in 2005, agriculture accounts for about 60% of N2O and about 50% of CH4 (medium agreement, medium evidence). Despite large annual exchanges of CO2 between the atmosphere and agricultural lands, the net flux is estimated to be approximately balanced, with CO2 emissions around 0.04 GtCO2/yr only (emissions from electricity and fuel use are covered in the buildings and transport sector, respectively) (low agreement, limited evidence). Globally, agricultural CH4 and N2O emissions have increased by nearly 17% from 1990 to 2005, an average annual emission increase of about 60 MtCO2-eq/yr. During that period, the five regions composed of Non-Annex I countries showed a 32% increase, and were, by 2005, responsible for about threequarters of total agricultural emissions. The other five regions, mostly Annex I countries, collectively showed a decrease of 12% in the emissions of these gases (high agreement, much evidence). A variety of options exists for mitigation of GHG emissions in agriculture. The most prominent options are improved crop and grazing land management (e.g., improved agronomic practices, nutrient use, tillage, and residue management), restoration of organic soils that are drained for crop production and restoration of degraded lands. Lower but still significant mitigation is possible with improved water and rice management; set-asides, land use change (e.g., conversion of cropland to grassland) and agro-forestry; as well as improved livestock and manure management. Many mitigation opportunities use current technologies and can be implemented immediately, but technological development will be a key driver ensuring the efficacy of additional mitigation measures in the future (high agreement, much evidence). Agricultural GHG mitigation options are found to be cost competitive with non-agricultural options (e.g., energy, transportation, forestry) in achieving long-term (i.e., 2100) climate objectives. Global long-term modelling suggests that non-CO2 crop and livestock abatement options could cost-effectively contribute 270–1520 MtCO2-eq/yr globally in 2030 with carbon prices up to 20 US$/tCO2-eq and 640–1870 MtCO2-eq/yr with C prices up to 50 US$/tCO2-eq Soil carbon management options are not currently considered in long-term modelling (medium agreement, limited evidence).
Considering all gases, the global technical mitigation potential from agriculture (excluding fossil fuel offsets from biomass) by 2030 is estimated to be ~5500-6,000 MtCO2-eq/yr (medium agreement, medium evidence). Economic potentials are estimated to be 1500-1600, 2500-2700, and 4000-4300 MtCO2-eq/yr at carbon prices of up to 20, 50 and 100 US$/ tCO2-eq, respectively About 70% of the potential lies in nonOECD/EIT countries, 20% in OECD countries and 10% for EIT countries (medium agreement, limited evidence). Soil carbon sequestration (enhanced sinks) is the mechanism responsible for most of the mitigation potential (high agreement, much evidence), with an estimated 89% contribution to the technical potantial. Mitigation of CH4 emissions and N2O emissions from soils account for 9% and 2%, respectively, of the total mitigation potential (medium agreement, medium evidence). The upper and lower limits about the estimates are largely determined by uncertainty in the per-area estimate for each mitigation measure. Overall, principal sources of uncertainties inherent in these mitigation potentials include: a) future level of adoption of mitigation measures (as influenced by barriers to adoption); b) effectiveness of adopted measures in enhancing carbon sinks or reducing N2O and CH4 emissions (particularly in tropical areas; reflected in the upper and lower bounds given above); and c) persistence of mitigation, as influenced by future climatic trends, economic conditions, and social behaviour (medium agreement, limited evidence). The role of alternative strategies changes across the range of prices for carbon. At low prices, dominant strategies are those consistent with existing production such as changes in tillage, fertilizer application, livestock diet formulation, and manure management. Higher prices elicit land-use changes that displace existing production, such as biofuels, and allow for use of costly animal feed-based mitigation options. A practice effective in reducing emissions at one site may be less effective or even counterproductive elsewhere. Consequently, there is no universally applicable list of mitigation practices; practices need to be evaluated for individual agricultural systems based on climate, edaphic, social setting, and historical patterns of land use and management (high agreement, much evidence). GHG emissions could also be reduced by substituting fossil fuels with energy produced from agricultural feed stocks (e.g., crop residues, dung, energy crops), which would be counted in sectors using the energy. The contribution of agriculture to the mitigation potential by using bioenergy depends on relative prices of the fuels and the balance of supply and demand. Using top-down models that include assumptions on such a balance the economic mitigation potential for agriculture in 2030 is estimated to be 70-1260 MtCO2-eq/yr at up to 20 US$/tCO2-eq, and 560-2320 MtCO2-eq/yr at up to 50 US$/tCO2-eq There are no estimates for the additional potential from top down models at carbon prices up to 100 US$/tCO2-eq, but the estimate for prices above 100 US$/tCO2-eq is 2720 MtCO2-eq/yr. These potentials represent mitigation of 5-80%, and 20-90% of all 499
Agriculture
other agricultural mitigation measures combined, at carbon prices of up to 20, and up to50 US$/tCO2-eq, respectively. An additional mitigation of 770 MtCO2-eq/yr could be achieved by 2030 by improved energy efficiency in agriculture, though the mitigation potential is counted mainly in the buildings and transport sectors (medium agreement, medium evidence). Agricultural mitigation measures often have synergy with sustainable development policies, and many explicitly influence social, economic, and environmental aspects of sustainability. Many options also have co-benefits (improved efficiency, reduced cost, environmental co-benefits) as well as trade-offs (e.g., increasing other forms of pollution), and balancing these effects will be necessary for successful implementation (high agreement, much evidence). There are interactions between mitigation and adaptation in the agricultural sector, which may occur simultaneously, but differ in their spatial and geographic characteristics. The main climate change benefits of mitigation actions will emerge over decades, but there may also be short-term benefits if the drivers achieve other policy objectives. Conversely, actions to enhance adaptation to climate change impacts will have consequences in the short and long term. Most mitigation measures are likely robust to future climate change (e.g., nutrient management), but a subset will likely be vulnerable (e.g., irrigation in regions becoming more arid). It may be possible for a vulnerable practice to be modified as the climate changes and to maintain the efficacy of a mitigation measure (low agreement, limited evidence).
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In many regions, non-climate policies related to macroeconomics, agriculture and the environment, have a larger impact on agricultural mitigation than climate policies (high agreement, much evidence). Despite significant technical potential for mitigation in agriculture, there is evidence that little progress has been made in the implementation of mitigation measures at the global scale. Barriers to implementation are not likely to be overcome without policy/economic incentives and other programmes, such as those promoting global sharing of innovative technologies. Current GHG emission rates may escalate in the future due to population growth and changing diets (high agreement, medium evidence). Greater demand for food could result in higher emissions of CH4 and N2O if there are more livestock and greater use of nitrogen fertilizers (high agreement, much evidence). Deployment of new mitigation practices for livestock systems and fertilizer applications will be essential to prevent an increase in emissions from agriculture after 2030. In addition, soil carbon may be more vulnerable to loss with climate change and other pressures, though increases in production will offset some or all of this carbon loss (low agreement, limited evidence). Overall, the outlook for GHG mitigation in agriculture suggests that there is significant potential (high agreement, medium evidence). Current initiatives suggest that synergy between climate change policies, sustainable development and improvement of environmental quality will likely lead the way forward to realize the mitigation potential in this sector.
Chapter 8
Agriculture
8.1
Introduction
Agriculture releases to the atmosphere significant amounts of CO2, CH4, and N2O (Cole et al., 1997; IPCC, 2001a; Paustian et al., 2004). CO2 is released largely from microbial decay or burning of plant litter and soil organic matter (Smith, 2004b; Janzen, 2004). CH4 is produced when organic materials decompose in oxygen-deprived conditions, notably from fermentative digestion by ruminant livestock, from stored manures, and from rice grown under flooded conditions (Mosier et al. 1998). N2O is generated by the microbial transformation of nitrogen in soils and manures, and is often enhanced where available nitrogen (N) exceeds plant requirements, especially under wet conditions (Oenema et al., 2005; Smith and Conen, 2004). Agricultural greenhouse gas (GHG) fluxes are complex and heterogeneous, but the active management of agricultural systems offers possibilities for mitigation. Many of these mitigation opportunities use current technologies and can be implemented immediately. This chapter describes the development of GHG emissions from the agricultural sector (Section 8.2), and details agricultural practices that may mitigate GHGs (Section 8.4.1), with many practices affecting more than one GHG by more than one mechanism. These practices include: cropland management; grazing land management/pasture improvement; management of agricultural organic soils; restoration of degraded lands; livestock management; manure/bio-solid management; and bio-energy production. It is theoretically possible to increase carbon storage in longlived agricultural products (e.g., strawboards, wool, leather, bio-plastics) but the carbon held in these products has only increased from 37 to 83 MtC per year over the past 40 years. Assuming a first order decay rate of 10 to 20 % per year, this
is estimated to be a global net annual removal of 3 to 7 MtCO2 from the atmosphere, which is negligible compared to other mitigation measures. The option is not considered further here. Smith et al. (2007a) recently estimated a global potential mitigation of 770 MtCO2-eq/yr by 2030 from improved energy efficiency in agriculture (e.g., through reduced fossil fuel use), However, this is usually counted in the relevant user sector rather than in agriculture and so is not considered further here. Any savings from improved energy efficiency are discussed in the relevant sections elsewhere in this volume, according to where fossil fuel savings are made, for example, from transport fuels (Chapter 5), or through improved building design (Chapter 6).
8.2 Status of sector, development trends including production and consumption, and implications Population pressure, technological change, public policies, and economic growth and the cost/price squeeze have been the main drivers of change in the agricultural sector during the last four decades. Production of food and fibre has more than kept pace with the sharp increase in demand in a more populated world. The global average daily availability of calories per capita has increased (Gilland, 2002), with some notable regional exceptions. This growth, however, has been at the expense of increased pressure on the environment, and depletion of natural resources (Tilman et al., 2001; Rees, 2003), while it has not resolved the problems of food security and child malnutrition suffered in poor countries (Conway and Toenniessen, 1999). Agricultural land occupied 5023 Mha in 2002 (FAOSTAT, 2006). Most of this area was under pasture (3488 Mha, or 69%)
Table 8.1. Agricultural land use in the last four decades. Area (Mha) 1961-70
1971-80
1981-90
1991-00
2001-02
Change 2000s/1960s % Mha
Agricultural land Arable land Permanent crops Permanent pasture 2. Developed countries
4,562 1,297 82 3,182
4,684 1,331 92 3,261
4,832 1,376 104 3,353
4,985 1,393 123 3,469
5,023 1,405 130 3,488
+10 +8 +59 +10
461 107 49 306
Agricultural land Arable land Permanent crops Permanent pasture 3. Developing countries
1,879 648 23 1,209
1,883 649 24 1,210
1,877 652 24 1,201
1,866 633 24 1,209
1,838 613 24 1,202
-2 -5 +4 -1
-41 -35 1 -7
Agricultural land Arable land Permanent crops Permanent pasture
2,682 650 59 1,973
2,801 682 68 2,051
2,955 724 80 2,152
3,119 760 99 2,260
3,184 792 106 2,286
+19 +22 +81 +16
502 142 48 313
1. World
Source: FAOSTAT, 2006.
501
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1.4
Chapter 8
are low. Meat demand in developing countries rose from 11 to 24 kg/capita/yr during the period 1967-1997, achieving an annual growth rate of more than 5% by the end of that period. Rosegrant et al. (2001) forecast a further increase of 57% in global meat demand by 2020, mostly in South and Southeast Asia, and Sub-Saharan Africa. The greatest increases in demand are expected for poultry (83 % by 2020; Roy et al., 2002).
ha developed countries developing countries
1.2 1
pasture
pasture
0.8 0.6 0.4
arable arable
0.2 0 1960
1970
1980
1990
2000
Figure 8.1. Per-capita area of arable land and pasture, in developed and developing countries. Source: FAOSTAT, 2006.
and cropland occupied 1405 Mha (28%). During the last four decades, agricultural land gained almost 500 Mha from other land uses, a change driven largely by increasing demands for food from a growing population. Every year during this period, an average 6 Mha of forestland and 7 Mha of other land were converted to agriculture, a change occurring largely in the developing world (Table 8.1). This trend is projected to continue into the future (Huang et al., 2002; Trewavas, 2002; Fedoroff and Cohen, 1999; Green et al., 2005), and Rosegrant et al., (2001) project that an additional 500 Mha will be converted to agriculture during 1997-2020, mostly in Latin America and Sub-Saharan Africa. Technological progress has made it possible to achieve remarkable improvements in land productivity, increasing percapita food availability (Table 8.2), despite a consistent decline in per-capita agricultural land (Figure 8.1). The share of animal products in the diet has increased consistently in the developing countries, while remaining constant in developed countries (Table 8.2). Economic growth and changing lifestyles in some developing countries are causing a growing demand for meat and dairy products, notably in China where current demands
Annual GHG emissions from agriculture are expected to increase in coming decades (included in the baseline) due to escalating demands for food and shifts in diet. However, improved management practices and emerging technologies may permit a reduction in emissions per unit of food (or of protein) produced. The main trends in the agricultural sector with the implications for GHG emissions or removals are summarized as follows: • Growth in land productivity is expected to continue, although at a declining rate, due to decreasing returns from further technological progress, and greater use of marginal land with lower productivity. Use of these marginal lands increases the risk of soil erosion and degradation, with highly uncertain consequences for CO2 emissions (Lal, 2004a; Van Oost et al., 2004). • Conservation tillage and zero-tillage are increasingly being adopted, thus reducing the use of energy and often increasing carbon storage in soils. According to FAO (2001), the worldwide area under zero-tillage in 1999 was approximately 50 Mha, representing 3.5% of total arable land. However, such practices are frequently combined with periodical tillage, thus making the assessment of the GHG balance highly uncertain. • Further improvements in productivity will require higher use of irrigation and fertilizer, increasing the energy demand (for moving water and manufacturing fertilizer; Schlesinger, 1999). Also, irrigation and N fertilization can increase GHG emissions (Mosier, 2001). • Growing demand for meat may induce further changes in land use (e.g., from forestland to grassland), often increasing CO2 emissions, and increased demand for animal
Table 8.2: Per capita food supply in developed and developing countries Change 2000s/1960s % cal/d or g/d
1961-70
1971-80
1981-90
1991-00
2001-02
Energy, all sources (cal/day) % from animal sources Protein, all sources (g/day) % from animal sources 2. Developing countries
3049 27 92 50
3181 28 97 55
3269 28 101 57
3223 27 99 56
3309 26 100 56
+9 -2 +9 +12
261 -8 --
Energy, all sources (cal/day) % from animal sources Protein, all sources (g/day) % from animal sources
2032 8 9 18
2183 8 11 20
2443 9 13 22
2600 12 18 28
2657 13 21 30
+31 +77 +123 +67
625 -48 --
1. Developed countries
Source: FAOSTAT, 2006.
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feeds (e.g., cereals). Larger herds of beef cattle will cause increased emissions of CH4 and N2O, although use of intensive systems (with lower emissions per unit product) is expected to increase faster than growth in grazing-based systems. This may attenuate the expected rise in GHG emissions. • Intensive production of beef, poultry, and pork is increasingly common, leading to increases in manure with consequent increases in GHG emissions. This is particularly true in the developing regions of South and East Asia, and Latin America, as well as in North America. • Changes in policies (e.g., subsidies), and regional patterns of production and demand are causing an increase in international trade of agricultural products. This is expected to increase CO2 emissions, due to greater use of energy for transportation. • There is an emerging trend for greater use of agricultural products (e.g., bio-plastics bio-fuels and biomass for energy) as substitutes for fossil fuel-based products. This has the potential to reduce GHG emissions in the future.
8.3
Emission trends (global and regional)
With an estimated global emission of non-CO2 GHGs from agriculture of between 5120 MtCO2-eq/yr (Denman et al., 2007) and 6116 MtCO2-eq/yr (US-EPA, 2006a) in 2005, agriculture accounts for 10-12 % of total global anthropogenic emissions of GHGs. Agriculture contributes about 47% and 58% of total anthropogenic emissions of CH4 and N2O, respectively, with a wide range of uncertainty in the estimates of both the agricultural contribution and the anthropogenic total. N2O emissions from soils and CH4 from enteric fermentation constitute the largest sources, 38% and 32% of total non-CO2 emissions from agriculture in 2005, respectively (US-EPA, 2006a). Biomass burning (12%), rice production (11%), and manure management (7%) account for the rest. CO2 emissions from agricultural soils are not normally estimated separately, but are included in the land use, land use change and forestry sector (e.g., in national GHG inventories). So there are few comparable estimates of emissions of this gas in agriculture. Agricultural lands generate very large CO2 fluxes both to and from the atmosphere (IPCC, 2001a), but the net flux is small. US-EPA, 2006b) estimated a net CO2 emission of 40 MtCO2-eq from agricultural soils in 2000, less than 1% of global anthropogenic CO2 emissions.
the other three regions - Latin America and The Caribbean, the countries of Eastern Europe, the Caucasus and Central Asia, and OECD Pacific - CH4 from enteric fermentation was the dominant source (US-EPA, 2006a). This is due to the large livestock population in these three regions which, in 2004, had a combined stock of cattle and sheep equivalent to 36% and 24% of world totals, respectively (FAO, 2003). Emissions from rice production and burning of biomass were heavily concentrated in the group of developing countries, with 97% and 92% of world totals, respectively. While CH4 emissions from rice occurred mostly in South and East Asia, where it is a dominant food source (82% of total emissions), those from biomass burning originated in Sub-Saharan Africa and Latin America and the Caribbean (74% of total). Manure management was the only source for which emissions where higher in the group of developed regions (52%) than in developing regions (48%; US-EPA, 2006a). The balance between the large fluxes of CO2 emissions and removals in agricultural land is uncertain. A study by USEPA (2006b) showed that some countries and regions have net emissions, while others have net removals of CO2. Except for the countries of Eastern Europe, the Caucasus and Central Asia, which had an annual emission of 26 MtCO2/yr in 2000, all other countries showed very low emissions or removals. 8.3.1
Globally, agricultural CH4 and N2O emissions increased by 17% from 1990 to 2005, an average annual emission increase of 58 MtCO2-eq/yr (US-EPA, 2006a). Both gases had about the same share of this increase. Three sources together explained 88% of the increase: biomass burning (N2O and CH4), enteric fermentation (CH4) and soil N2O emissions (US-EPA, 2006a). During that period, according to US-EPA (2006a; Figure 8.2), the five regions composed of Non-Annex I countries showed a 32% increase in non-CO2 emissions (equivalent to 73 MtCO2-eq/yr).The other five regions, with mostly Annex I countries, collectively showed a decrease of 12% (equivalent to 15 MtCO2-eq/yr). This was mostly due to non-climate macroeconomic policies in the Central and Eastern European and the countries of Eastern Europe, the Caucasus and Central Asia (see Section 8.7.1 and 8.7.2). 8.3.2
Both the magnitude of the emissions and the relative importance of the different sources vary widely among world regions (Figure 8.2). In 2005, the group of five regions mostly consisting of non-Annex I countries was responsible for 74% of total agricultural emissions. In seven of the ten regions, N2O from soils was the main source of GHGs in the agricultural sector in 2005, mainly associated with N fertilizers and manure applied to soils. In
Trends since 1990
Future global trends
Agricultural N2O emissions are projected to increase by 35-60% up to 2030 due to increased nitrogen fertilizer use and increased animal manure production (FAO, 2003). Similarly, Mosier and Kroeze (2000) and US-EPA (2006a; Figure 8.2) estimated that N2O emissions will increase by about 50% by 2020 (relative to 1990). If demands for food increase, and diets shift as projected, then annual emissions of GHGs from agriculture may escalate further. But improved management 503
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Developing countries of South Asia Mt CO2-eq
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Figure 8.2: Estimated historical and projected N2O and CH4 emissions in the agricultural sector of the ten world regions during the period 1990-2020. Source: Adapted from US-EPA, 2006a.
practices and emerging technologies may permit a reduction in emissions per unit of food (or protein) produced, and perhaps also a reduction in emissions per capita food consumption. If CH4 emissions grow in direct proportion to increases in livestock numbers, then global livestock-related methane production is expected to increase by 60% up to 2030 (FAO, 2003). However, changes in feeding practices and manure management could ameliorate this increase. US-EPA (2006a) forecast that combined methane emissions from enteric fermentation and manure management will increase by 21% between 2005 and 2020. The area of rice grown globally is forecast to increase by 4.5% to 2030 (FAO, 2003), so methane emissions from rice production would not be expected to increase substantially. There may even be reductions if less rice is grown under continuous flooding (causing anaerobic soil conditions) as a result of scarcity of water, or if new rice cultivars that emit 504
less methane are developed and adopted (Wang et al., 1997). However, US-EPA (2006a) projects a 16% increase in CH4 emissions from rice crops between 2005 and 2020, mostly due to a sustained increase in the area of irrigated rice. No baseline agricultural non-CO2 GHG emission estimates for the year 2030 have been published, but according to USEPA (2006a), aggregate emissions are projected to increase by ~13% during the decades 2000-2010 and 2010-2020. Assuming similar rates of increase (10-15%) for 2020-2030, agricultural emissions might be expected to rise to 8000–8400, with a mean of 8300 MtCO2-eq by 2030. The future evolution of CO2 emissions from agriculture is uncertain. Due to stable or declining deforestation rates (FAO, 2003), and increased adoption of conservation tillage practices (FAO, 2001), these emissions are likely to decrease or remain at low levels.
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8.3.3
Agriculture
Regional trends
The Middle East and North Africa, and Sub-Saharan Africa have the highest projected growth in emissions, with a combined 95% increase in the period 1990 to 2020 (US-EPA, 2006a). Sub-Saharan Africa is the one world region where percapita food production is either in decline, or roughly constant at a level that is less than adequate (Scholes and Biggs, 2004). This trend is linked to low and declining soil fertility (Sanchez, 2002), and inadequate fertilizer inputs. Although slow, the rising wealth of urban populations is likely to increase demand for livestock products. This would result in intensification of agriculture and expansion to still largely unexploited areas, particularly in South and Central Africa (including Angola, Zambia, DRC, Mozambique and Tanzania), with a consequent increase in GHG emissions. East Asia is projected to show large increases in GHG emissions from animal sources. According to FAO (FAOSTAT, 2006), total production of meat and milk in Asian developing countries increased more than 12 times and 4 times, respectively, from 2004 to 1961. Since the per-capita consumption of meat and milk is still much lower in these countries than in developed countries, increasing trends are expected to continue for a relatively long time. Accordingly, US-EPA (2006a) forecast increases of 153% and 86% in emissions from enteric fermentation and manure management, respectively, from 1990 to 2020. In South Asia, emissions are increasing mostly because of expanding use of N fertilizers and manure to meet demands for food, resulting from rapid population growth.
widespread application of intensive management technologies could result in a 2 to 2.5-fold rise in grain and fodder yields, with a consequent reduction of arable land, but may increase N fertilizer use. Decreases in fertilizer N use since 1990 have led to a significant reduction in N2O emissions. But, under favourable economic conditions, the amount of N fertilizer applied will again increase, although unlikely to reach pre-1990 levels in the near future. US-EPA (2006a) projected a 32% increase in N2O emissions from soils in these two regions between 2005 and 2020, equivalent to an average rate of increase of 3.5 MtCO2eq/yr. OECD North America and OECD Pacific are the only developed regions showing a consistent increase in GHG emissions in the agricultural sector (18% and 21%, respectively between 1990 and 2020; Figure 8.2). In both cases, the trend is largely driven by non-CO2 emissions from manure management and N2O emissions from soils. In Oceania, nitrogen fertilizer use has increased exponentially over the past 45 years with a 5 and 2.5 fold increase since 1990 in New Zealand and Australia, respectively. In North America, in contrast, nitrogen fertilizer use has remained stable; the main driver for increasing emissions is management of manure from cattle, poultry and swine production, and manure application to soils. In both regions, conservation policies have resulted in reduced CO2 emissions from land conversion. Land clearing in Australia has declined by 60% since 1990 with vegetation management policies restricting further clearing, while in North America, some marginal croplands have been returned to woodland or grassland.
In Latin America and the Caribbean, agricultural products are the main source of exports. Significant changes in land use and management have occurred, with forest conversion to cropland and grassland being the most significant, resulting in increased GHG emissions from soils (CO2 and N2O). The cattle population has increased linearly from 176 to 379 Mhead between 1961 and 2004, partly offset by a decrease in the sheep population from 125 to 80 Mhead. All other livestock categories have increased in the order of 30 to 600% since 1961. Cropland areas, including rice and soybean, and the use of N fertilizers have also shown dramatic increases (FAOSTAT, 2006). Another major trend in the region is the increased adoption of no-till agriculture, particularly in the Mercosur area (Brazil, Argentina, Paraguay, and Uruguay). This technology is used on ~30 Mha every year in the region, although it is unknown how much of this area is under permanent no-till.
Western Europe is the only region where, according to USEPA (2006a), GHG emissions from agriculture are projected to decrease to 2020 (Figure 8.2). This is associated with the adoption of a number of climate-specific and other environmental policies in the European Union, as well as economic constraints on agriculture, as discussed in Sections 8.7.1 and 8.7.2.
In the countries of Central and Eastern Europe, the Caucasus and Central Asia, agricultural production is, at present, about 60-80% of that in 1990, but is expected to grow by 15-40% above 2001 levels by 2010, driven by the increasing wealth of these countries. A 10-14% increase in arable land area is forecast for the whole of Russia due to agricultural expansion. The
Opportunities for mitigating GHGs in agriculture fall into three broad categories1, based on the underlying mechanism:
1
8.4 Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability
8.4.1
a.
Mitigation technologies and practices
Reducing emissions: Agriculture releases to the atmosphere significant amounts of CO2, CH4, or N2O (Cole et al., 1997; IPCC, 2001a; Paustian et al., 2004). The fluxes
Smith et al. (2007a) have recently reviewed mechanisms for agricultural GHG mitigation. This section draws largely from that study.
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of these gases can be reduced by more efficient management of carbon and nitrogen flows in agricultural ecosystems. For example, practices that deliver added N more efficiently to crops often reduce N2O emissions (Bouwman, 2001), and managing livestock to make most efficient use of feeds often reduces amounts of CH4 produced (Clemens and Ahlgrimm, 2001). The approaches that best reduce emissions depend on local conditions, and therefore, vary from region to region. b.
c.
Enhancing removals: Agricultural ecosystems hold large carbon reserves (IPCC, 2001a), mostly in soil organic matter. Historically, these systems have lost more than 50 Pg C (Paustian et al., 1998; Lal, 1999, 2004a), but some of this carbon lost can be recovered through improved management, thereby withdrawing atmospheric CO2. Any practice that increases the photosynthetic input of carbon and/or slows the return of stored carbon to CO2 via respiration, fire or erosion will increase carbon reserves, thereby ‘sequestering’ carbon or building carbon ‘sinks’. Many studies, worldwide, have now shown that significant amounts of soil carbon can be stored in this way, through a range of practices, suited to local conditions (Lal, 2004a). Significant amounts of vegetative carbon can also be stored in agro-forestry systems or other perennial plantings on agricultural lands (Albrecht and Kandji, 2003). Agricultural lands also remove CH4 from the atmosphere by oxidation (but less than forests; Tate et al., 2006), but this effect is small compared to other GHG fluxes (Smith and Conen, 2004).
mechanisms such as aerosols or albedo, those impacts also need to be considered (Marland et al., 2003b; Andreae et al., 2005). The impacts of the mitigation options considered are summarized qualitatively in Table 8.3. Although comprehensive life-cycle analyses are not always possible, given the complexity of many farming systems, the table also includes estimates of the confidence based on expert opinion that the practice can reduce overall net emissions at the site of adoption. Some of these practices also have indirect effects on ecosystems elsewhere. For example, increased productivity in existing croplands could avoid deforestation and its attendant emissions (see also Section 8.8). The most important options are discussed in Section 8.4.1. 8.4.1.1
Cropland management
Because often intensively managed, croplands offer many opportunities to impose practices that reduce net GHG emissions (Table 8.3). Mitigation practices in cropland management include the following partly-overlapping categories: a.
Agronomy: Improved agronomic practices that increase yields and generate higher inputs of carbon residue can lead to increased soil carbon storage (Follett, 2001). Examples of such practices include: using improved crop varieties; extending crop rotations, notably those with perennial crops that allocate more carbon below ground; and avoiding or reducing use of bare (unplanted) fallow (West and Post, 2002; Smith, 2004a, b; Lal, 2003, 2004a; Freibauer et al., 2004). Adding more nutrients, when deficient, can also promote soil carbon gains (Alvarez, 2005), but the benefits from N fertilizer can be offset by higher N2O emissions from soils and CO2 from fertilizer manufacture (Schlesinger, 1999; Pérez-Ramírez et al., 2003; Robertson, 2004; Gregorich et al., 2005). Emissions per hectare can also be reduced by adopting cropping systems with reduced reliance on fertilizers, pesticides and other inputs (and therefore, the GHG cost of their production: Paustian et al., 2004). An important example is the use of rotations with legume crops (West and Post, 2002; Izaurralde et al., 2001), which reduce reliance on external N inputs although legume-derived N can also be a source of N2O (Rochette and Janzen, 2005). Another group of agronomic practices are those that provide temporary vegetative cover between successive agricultural crops, or between rows of tree or vine crops. These ‘catch’ or ‘cover’ crops add carbon to soils (Barthès et al., 2004; Freibauer et al., 2004) and may also extract plantavailable N unused by the preceding crop, thereby reducing N2O emissions.
b.
Nutrient management: Nitrogen applied in fertilizers, manures, biosolids, and other N sources is not always used efficiently by crops (Galloway et al., 2003; Cassman et al., 2003). The surplus N is particularly susceptible to emission
Avoiding (or displacing) emissions: Crops and residues from agricultural lands can be used as a source of fuel, either directly or after conversion to fuels such as ethanol or diesel (Schneider and McCarl, 2003; Cannell, 2003). These bio-energy feedstocks still release CO2 upon combustion, but now the carbon is of recent atmospheric origin (via photosynthesis), rather than from fossil carbon. The net benefit of these bio-energy sources to the atmosphere is equal to the fossil-derived emissions displaced, less any emissions from producing, transporting, and processing. GHG emissions, notably CO2, can also be avoided by agricultural management practices that forestall the cultivation of new lands now under forest, grassland, or other non-agricultural vegetation (Foley et al., 2005).
Many practices have been advocated to mitigate emissions through the mechanisms cited above. Often, a practice will affect more than one gas, by more than one mechanism, sometimes in opposite ways, so the net benefit depends on the combined effects on all gases (Robertson and Grace, 2004; Schils et al., 2005; Koga et al., 2006). In addition, the temporal pattern of influence may vary among practices or among gases for a given practice; some emissions are reduced indefinitely, other reductions are temporary (Six et al., 2004; Marland et al., 2003a). Where a practice affects radiative forcing through other 506
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Table 8.3: Proposed measures for mitigating greenhouse gas emissions from agricultural ecosystems, their apparent effects on reducing emissions of individual gases where adopted (mitigative effect), and an estimate of scientific confidence that the proposed practice can reduce overall net emissions at the site of adoption. Mitigative effectsa Measure Cropland management
Grazing land management/ pasture improvement
Management of organic soils Restoration of degraded lands Livestock management
Manure/biosolid management Bio-energy
Examples Agronomy Nutrient management Tillage/residue management Water management (irrigation, drainage) Rice management Agro-forestry Set-aside, land-use change Grazing intensity Increased productivity (e.g., fertilization) Nutrient management Fire management Species introduction (including legumes) Avoid drainage of wetlands
CO2 + + + +/+/+ + +/+ + + + +
Erosion control, organic amendments, nutrient amendments Improved feeding practices Specific agents and dietary additives Longer term structural and management changes and animal breeding Improved storage and handling Anaerobic digestion More efficient use as nutrient source Energy crops, solid, liquid, biogas, residues
CH4
+ + +/-
+ -
+ + + + + + + +
+/-
N2O +/+ +/+ +/+/+ +/+/+/+/+/+/-
Net mitigationb (confidence) Agreement Evidence *** ** *** ** ** ** * * ** ** *** * *** *** * * ** * ** ** * * * ** ** **
+/-
***
**
+ +
*** ** **
*** *** *
+/+/+ +/-
*** *** *** ***
** * ** **
Notes: a + denotes reduced emissions or enhanced removal (positive mitigative effect); - denotes increased emissions or suppressed removal (negative mitigative effect); +/- denotes uncertain or variable response. b A qualitative estimate of the confidence in describing the proposed practice as a measure for reducing net emissions of greenhouse gases, expressed as CO2-eq: Agreement refers to the relative degree of consensus in the literature (the more asterisks, the higher the agreement); Evidence refers to the relative amount of data in support of the proposed effect (the more asterisks, the more evidence). Source: adapted from Smith et al., 2007a.
of N2O (McSwiney and Robertson, 2005). Consequently, improving N use efficiency can reduce N2O emissions and indirectly reduce GHG emissions from N fertilizer manufacture (Schlesinger, 1999). By reducing leaching and volatile losses, improved efficiency of N use can also reduce off-site N2O emissions. Practices that improve N use efficiency include: adjusting application rates based on precise estimation of crop needs (e.g., precision farming); using slow- or controlled-release fertilizer forms or nitrification inhibitors (which slow the microbial processes leading to N2O formation); applying N when least susceptible to loss, often just prior to plant uptake (improved timing); placing the N more precisely into the soil to make it more accessible to crops roots; or avoiding N applications in excess of immediate plant requirements (Robertson, 2004; Dalal et al., 2003; Paustian et al., 2004; Cole et al., 1997; Monteny et al., 2006).
c.
Tillage/residue management: Advances in weed control methods and farm machinery now allow many crops to be grown with minimal tillage (reduced tillage) or without tillage (no-till). These practices are now increasingly used throughout the world (e.g., Cerri et al., 2004). Since soil disturbance tends to stimulate soil carbon losses through enhanced decomposition and erosion (Madari et al., 2005), reduced- or no-till agriculture often results in soil carbon gain, but not always (West and Post, 2002; Ogle et al., 2005; Gregorich et al., 2005; Alvarez 2005). Adopting reduced- or no-till may also affect N2O, emissions but the net effects are inconsistent and not well-quantified globally (Smith and Conen, 2004; Helgason et al., 2005; Li et al., 2005; Cassman et al., 2003). The effect of reduced tillage on N2O emissions may depend on soil and climatic conditions. In some areas, reduced tillage promotes N2O emissions, while elsewhere it may reduce emissions or have no measurable influence (Marland et al., 2001). Fur507
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ther, no-tillage systems can reduce CO2 emissions from energy use (Marland et al., 2003b; Koga et al., 2006). Systems that retain crop residues also tend to increase soil carbon because these residues are the precursors for soil organic matter, the main carbon store in soil. Avoiding the burning of residues (e.g., mechanising sugarcane harvesting, eliminating the need for pre-harvest burning (Cerri et al., 2004)) also avoids emissions of aerosols and GHGs generated from fire, although CO2 emissions from fuel use may increase. d. Water management: About 18% of the world’s croplands now receive supplementary water through irrigation (Millennium Ecosystem Assessment, 2005). Expanding this area (where water reserves allow) or using more effective irrigation measures can enhance carbon storage in soils through enhanced yields and residue returns (Follett, 2001; Lal, 2004a). But some of these gains may be offset by CO2 from energy used to deliver the water (Schlesinger 1999; Mosier et al., 2005) or from N2O emissions from higher moisture and fertilizer N inputs (Liebig et al. 2005), The latter effect has not been widely measured. Drainage of croplands lands in humid regions can promote productivity (and hence soil carbon) and perhaps also suppress N2O emissions by improving aeration (Monteny et al., 2006). Any nitrogen lost through drainage, however, may be susceptible to loss as N2O.(Reay et al. 2003). e.
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Rice management: Cultivated wetland rice soils emit significant quantities of methane (Yan et al., 2003). Emissions during the growing season can be reduced by various practices (Yagi et al., 1997; Wassmann et al., 2000; Aulakh et al., 2001). For example, draining wetland rice once or several times during the growing season reduces CH4 emissions (Smith and Conen, 2004; Yan et al., 2003; Khalil and Shearer, 2006). This benefit, however, may be partly offset by increased N2O emissions (Akiyama et al. 2005), and the practice may be constrained by water supply. Rice cultivars with low exudation rates could offer an important methane mitigation option (Aulakh et al., 2001). In the off-rice season, methane emissions can be reduced by improved water management, especially by keeping the soil as dry as possible and avoiding water logging (Cai et al., 2000 2003; Kang et al., 2002; Xu et al., 2003). Increasing rice production can also enhance soil organic carbon stocks (Pan et al., 2006). Methane emissions can be reduced by adjusting the timing of organic residue additions (e.g., incorporating organic materials in the dry period rather than in flooded periods; Xu et al., 2000; Cai and Xu, 2004), by composting the residues before incorporation, or by producing biogas for use as fuel for energy production (Wang and Shangguan, 1996; Wassmann et al., 2000).
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f.
Agro-forestry: Agro-forestry is the production of livestock or food crops on land that also grows trees for timber, firewood, or other tree products. It includes shelter belts and riparian zones/buffer strips with woody species. The standing stock of carbon above ground is usually higher than the equivalent land use without trees, and planting trees may also increase soil carbon sequestration (Oelbermann et al., 2004; Guo and Gifford, 2002; Mutuo et al., 2005; Paul et al., 2003). But the effects on N2O and CH4 emissions are not well known (Albrecht and Kandji, 2003).
g.
Land cover (use) change: One of the most effective methods of reducing emissions is often to allow or encourage the reversion of cropland to another land cover, typically one similar to the native vegetation. The conversion can occur over the entire land area (‘set-asides’), or in localized spots, such as grassed waterways, field margins, or shelterbelts (Follett, 2001; Freibauer et al., 2004; Lal, 2004b; Falloon et al., 2004; Ogle et al., 2003). Such land cover change often increases carbon storage. For example, converting arable cropland to grassland typically results in the accrual of soil carbon because of lower soil disturbance and reduced carbon removal in harvested products. Compared to cultivated lands, grasslands may also have reduced N2O emissions from lower N inputs, and higher rates of CH4 oxidation, but recovery of oxidation may be slow (Paustian et al., 2004). Similarly, converting drained croplands back to wetlands can result in rapid accumulation of soil carbon (removal of atmospheric CO2). This conversion may stimulate CH4 emissions because water logging creates anaerobic conditions (Paustian et al., 2004). Planting trees can also reduce emissions. These practices are considered under agro-forestry (Section 8.4.1.1f); afforestation (Chapter 9), and reafforestation (Chapter 9). Because land cover (or use) conversion comes at the expense of lost agricultural productivity, it is usually an option only on surplus agricultural land or on croplands of marginal productivity.
8.4.1.2
Grazing land management and pasture improvement
Grazing lands occupy much larger areas than croplands (FAOSTAT, 2006) and are usually managed less intensively. The following are examples of practices to reduce GHG emissions and to enhance removals: a.
Grazing intensity: The intensity and timing of grazing can influence the removal, growth, carbon allocation, and flora of grasslands, thereby affecting the amount of carbon accrual in soils (Conant et al., 2001; 2005; Freibauer et al., 2004; Conant and Paustian, 2002; Reeder et al., 2004). Carbon accrual on optimally grazed lands is often greater than on ungrazed or overgrazed lands (Liebig et al., 2005; Rice and Owensby, 2001). The effects are inconsistent, however, owing to the many types of grazing practices
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employed and the diversity of plant species, soils, and climates involved (Schuman et al., 2001; Derner et al., 2006). The influence of grazing intensity on emission of non-CO2 gases is not well-established, apart from the direct effects on emissions from adjustments in livestock numbers. b.
c.
d.
Increased productivity: (including fertilization): As for croplands, carbon storage in grazing lands can be improved by a variety of measures that promote productivity. For instance, alleviating nutrient deficiencies by fertilizer or organic amendments increases plant litter returns and, hence, soil carbon storage (Schnabel et al., 2001; Conant et al., 2001). Adding nitrogen, however, often stimulates N2O emissions (Conant et al., 2005) thereby offsetting some of the benefits. Irrigating grasslands, similarly, can promote soil carbon gains (Conant et al., 2001). The net effect of this practice, however, depends also on emissions from energy use and other activities on the irrigated land (Schlesinger, 1999). Nutrient management: Practices that tailor nutrient additions to plant uptake, such as those described for croplands, can reduce N2O emissions (Dalal et al., 2003; Follett et al., 2001). Management of nutrients on grazing lands, however, may be complicated by deposition of faeces and urine from livestock, which are not as easily controlled nor as uniformly applied as nutritive amendments in croplands (Oenema et al., 2005). Fire management: On-site biomass burning (not to be confused with bio-energy, where biomass is combusted off-site for energy) contributes to climate change in several ways. Firstly, it releases GHGs, notably CH4 and, and to a lesser extent, N2O (the CO2 released is of recent origin, is absorbed by vegetative regrowth, and is usually not included in GHG inventories). Secondly, it generates hydrocarbon and reactive nitrogen emissions, which react to form tropospheric ozone, a powerful GHG. Thirdly, fires produce a range of smoke aerosols which can have either warming or cooling effects on the atmosphere; the net effect is thought to be positive radiative forcing (Andreae et al., 2005; Jones et al., 2003; Venkataraman et al., 2005; Andreae, 2001; Andreae and Merlet, 2001; Anderson et al., 2003; Menon et al., 2002). Fourth, fire reduces the albedo of the land surface for several weeks, causing warming (Beringer et al., 2003). Finally, burning can affect the proportion of woody versus grass cover, notably in savannahs, which occupy about an eighth of the global land surface. Reducing the frequency or intensity of fires typically leads to increased tree and shrub cover, resulting in a CO2 sink in soil and biomass (Scholes and van der Merwe, 1996). This woodyplant encroachment mechanism saturates over 20-50 years, whereas avoided CH4 and N2O emissions continue as long as fires are suppressed. Mitigation actions involve reducing the frequency or extent of fires through more effective fire suppression; re-
ducing the fuel load by vegetation management; and burning at a time of year when less CH4 and N2O are emitted (Korontzi et al., 2003). Although most agricultural-zone fires are ignited by humans, there is evidence that the area burned is ultimately under climatic control (Van Wilgen et al., 2004). In the absence of human ignition, the fire-prone ecosystems would still burn as a result of climatic factors. e.
Species introduction: Introducing grass species with higher productivity, or carbon allocation to deeper roots, has been shown to increase soil carbon. For example, establishing deep-rooted grasses in savannahs has been reported to yield very high rates of carbon accrual (Fisher et al., 1994), although the applicability of these results has not been widely confirmed (Conant et al., 2001; Davidson et al., 1995). In the Brazilian Savannah (Cerrado Biome), integrated crop-livestock systems using Brachiaria grasses and zero tillage are being adopted (Machado and Freitas, 2004). Introducing legumes into grazing lands can promote soil carbon storage (Soussana et al., 2004), through enhanced productivity from the associated N inputs, and perhaps also reduced emissions from fertilizer manufacture if biological N2 fixation displaces applied N fertilizer N (Sisti et al., 2004; Diekow et al., 2005). Ecological impacts of species introduction need to be considered.
Grazing lands also emit GHGs from livestock, notably CH4 from ruminants and their manures. Practices for reducing these emissions are considered under Section 8.4.1.5: Livestock management. 8.4.1.3 Management of organic/peaty soils Organic or peaty soils contain high densities of carbon accumulated over many centuries because decomposition is suppressed by absence of oxygen under flooded conditions. To be used for agriculture, these soils are drained, which aerates the soil, favouring decomposition and therefore, high CO2 and N2O fluxes. Methane emissions are usually suppressed after draining, but this effect is far outweighed by pronounced increases in N2O and CO2 (Kasimir-Klemedtsson et al., 1997). Emissions from drained organic soils can be reduced to some extent by practices such as avoiding row crops and tubers, avoiding deep ploughing, and maintaining a shallower water table. But the most important mitigation practice is avoiding the drainage of these soils in the first place or re-establishing a high water table (Freibauer et al., 2004). 8.4.1.4 Restoration of degraded lands A large proportion of agricultural lands has been degraded by excessive disturbance, erosion, organic matter loss, salinization, acidification, or other processes that curtail productivity (Batjes, 1999; Foley et al., 2005; Lal, 2001a, 2003, 2004b). Often, carbon storage in these soils can be partly restored by practices that reclaim productivity including: re-vegetation (e.g., planting 509
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• Halogenated compounds inhibit methanogenic bacteria (Wolin et al., 1964; Van Nevel and Demeyer, 1995) but their effects, too, are often transitory and they can have side-effects such as reduced intake. • Novel plant compounds such as condensed tannins (Pinares-Patiño et al., 2003; Hess et al., 2006), saponins (Lila et al., 2003) or essential oils (Patra et al., 2006; Kamra et al., 2006) may have merit in reducing methane emissions, but these responses may often be obtained through reduced digestibility of the diet. • Probiotics, such as yeast culture, have shown only small, insignificant effects (McGinn et al., 2004), but selecting strains specifically for methane-reducing ability could improve results (Newbold and Rode, 2006). • Propionate precursors such as fumarate or malate reduce methane formation by acting as alternative hydrogen acceptors (Newbold et al., 2002). But as response is elicited only at high doses, propionate precursors are, therefore, expensive (Newbold et al., 2005). • Vaccines against methanogenic bacteria are being developed but are not yet available commercially (Wright et al., 2004). • Bovine somatotropin (bST) and hormonal growth implants do not specifically suppress CH4 formation, but by improving animal performance (Bauman, 1992; Schmidely, 1993), they can reduce emissions per-kg of animal product (Johnson et al., 1991; McCrabb, 2001).
grasses); improving fertility by nutrient amendments; applying organic substrates such as manures, biosolids, and composts; reducing tillage and retaining crop residues; and conserving water (Lal, 2001b; 2004b; Bruce et al., 1999; Olsson and Ardö, 2002; Paustian et al., 2004). Where these practices involve higher nitrogen amendments, the benefits of carbon sequestration may be partly offset by higher N2O emissions. 8.4.1.5
Livestock management
Livestock, predominantly ruminants such as cattle and sheep, are important sources of CH4, accounting for about one-third of global anthropogenic emissions of this gas (US-EPA, 2006a). The methane is produced primarily by enteric fermentation and voided by eructation (Crutzen, 1995; Murray et al., 1976; Kennedy and Milligan, 1978). All livestock generate N2O emissions from manure as a result of excretion of N in urine and faeces. Practices for reducing CH4 and N2O emissions from this source fall into three general categories: improved feeding practices, use of specific agents or dietary additives; and longerterm management changes and animal breeding (Soliva et al., 2006; Monteny et al., 2006). a.
Improved feeding practices: Methane emissions can be reduced by feeding more concentrates, normally replacing forages (Blaxter and Claperton, 1965; Johnson and Johnson, 1995; Lovett et al., 2003; Beauchemin and McGinn, 2005). Although concentrates may increase daily methane emissions per animal, emissions per kgfeed intake and per kg-product are almost invariably reduced. The magnitude of this reduction per kg-product decreases as production increases. The net benefit of concentrates, however, depends on reduced animal numbers or younger age at slaughter for beef animals, and on how the practice affects land use, the N content of manure and emissions from producing and transporting the concentrates (Phetteplace et al., 2001; Lovett et al., 2006). Other practices that can reduce CH4 emissions include: adding certain oils or oilseeds to the diet (e.g., Machmüller et al., 2000; Jordan et al., 2006c); improving pasture quality, especially in less developed regions, because this improves animal productivity, and reduces the proportion of energy lost as CH4 (Leng, 1991; McCrabb et al., 1998; Alcock and Hegarty, 2006); and optimizing protein intake to reduce N excretion and N2O emissions (Clark et al., 2005).
c.
Longer-term management changes and animal breeding: Increasing productivity through breeding and better management practices, such as a reduction in the number of replacement heifers, often reduces methane output per unit of animal product (Boadi et al., 2004). Although selecting cattle directly for reduced methane production has been proposed (Kebreab et al., 2006), it is still impractical due to difficulties in accurately measuring methane emissions at a magnitude suitable for breeding programmes. With improved efficiency, meat-producing animals reach slaughter weight at a younger age, with reduced lifetime emissions (Lovett and O’Mara, 2002). However, the whole-system effects of such practices may not always lead to reduced emissions. For example in dairy cattle, intensive selection for higher yield may reduce fertility, requiring more replacement heifers in the herd (Lovett et al., 2006).
8.4.1.6 Manure management b.
510
Specific agents and dietary additives: A wide range of specific agents, mostly aimed at suppressing methanogenesis, has been proposed as dietary additives to reduce CH4 emissions: • Ionophores are antibiotics that can reduce methane emissions (Benz and Johnson, 1982; Van Nevel and Demeyer, 1996; McGinn et al., 2004), but their effect may be transitory (Rumpler et al., 1986); and they have been banned in the EU.
Animal manures can release significant amounts of N2O and CH4 during storage, but the magnitude of these emissions varies. Methane emissions from manure stored in lagoons or tanks can be reduced by cooling, use of solid covers, mechanically separating solids from slurry, or by capturing the CH4 emitted (Amon et al. 2006; Clemens and Ahlgrimm, 2001; Monteny et al. 2001, 2006; Paustian et al., 2004). The manures can also be digested anaerobically to maximize CH4 retrieval as a renewable
Chapter 8
energy source (Clemens and Ahlgrimm, 2001; Clemens et al., 2006). Handling manures in solid form (e.g., composting) rather than liquid form can suppress CH4 emissions, but may increase N2O formation (Paustian et al., 2004). Preliminary evidence suggests that covering manure heaps can reduce N2O emissions, but the effect of this practice on CH4 emissions is variable (Chadwick, 2005). For most animals, worldwide there is limited opportunity for manure management, treatment, or storage; excretion happens in the field and handling for fuel or fertility amendment occurs when it is dry and methane emissions are negligible (Gonzalez-Avalos and Ruiz-Suarez, 2001). To some extent, emissions from manure might be curtailed by altering feeding practices (Külling et al., 2003; Hindrichsen et al., 2006; Kreuzer and Hindrichsen, 2006), or by composting the manure (Pattey et al., 2005; Amon et al., 2001), but if aeration is inadequate CH4 emissions during composting can still be substantial (Xu et al., 2007). All of these practices require further study from the perspective of their impact on whole life-cycle GHG emissions. Manures also release GHGs, notably N2O, after application to cropland or deposition on grazing lands. Practices for reducing these emissions are considered in Subsection 8.4.1.1: Cropland management and Subsection 8.4.1.2: Grazing land management. 8.4.1.7 Bioenergy Increasingly, agricultural crops and residues are seen as sources of feedstocks for energy to displace fossil fuels. A wide range of materials have been proposed for use, including grain, crop residue, cellulosic crops (e.g., switchgrass, sugarcane), and various tree species (Edmonds, 2004; Cerri et al., 2004; Paustian et al., 2004; Sheehan et al., 2004; Dias de Oliveira et al., 2005; Eidman, 2005). These products can be burned directly, but can also be processed further to generate liquid fuels such as ethanol or diesel fuel (Richter, 2004). Such fuels release CO2 when burned, but this CO2 is of recent atmospheric origin (via photosynthetic carbon uptake) and displaces CO2 which otherwise would have come from fossil carbon. The net benefit to atmospheric CO2, however, depends on energy used in growing and processing the bioenergy feedstock (Spatari et al., 2005). The competition for other land uses and the environmental impacts need to be considered when planning to use energy crops (e.g., European Environment Agency, 2006). The interactions of an expanding bioenergy sector with other land uses, and impacts on agro-ecosystem services such as food production, biodiversity, soil and nature conservation, and carbon sequestration have not yet been adequately studied, but bottom-up approaches (Smeets et al., 2007) and integrated assessment modelling (Hoogwijk et al., 2005; Hoogwijk, 2004)
2
Agriculture
offer opportunities to improve understanding. Latin America, Sub-Saharan Africa, and Eastern Europe are promising regions for bio-energy, with additional long-term contributions from Oceania and East and Northeast Asia. The technical potential for biomass production may be developed at low production costs in the range of 2 US$/GJ (Hoogwijk, 2004; Rogner et al., 2000). Major transitions are required to exploit the large potential for bioenergy. Improving agricultural efficiency in developing countries is a key factor. It is still uncertain to what extent, and how fast, such transitions could be realized in different regions. Under less favourable conditions, the regional bioenergy potential(s) could be quite low. Also, technological developments in converting biomass to energy, as well as long distance biomass supply chains (e.g., those involving intercontinental transport of biomass derived energy carriers) can dramatically improve competitiveness and efficiency of bio-energy (Faaij, 2006; Hamelinck et al., 2004). 8.4.2
Mitigation technologies and practices: perarea estimates of potential
As mitigation practices can affect more than one GHG2, it is important to consider the impact of mitigation options on all GHGs (Robertson et al,. 2000; Smith et al., 2001; Gregorich et al., 2005). For non-livestock mitigation options, ranges for perarea mitigation potentials of each GHG are provided in Table 8.4 (tCO2-eq/ha/yr). Mitigation potentials for CO2 represent the net change in soil carbon pools, reflecting the accumulated difference between carbon inputs to the soil after CO2 uptake by plants, and release of CO2 by decomposition in soil. Mitigation potentials for N2O and CH4 depend solely on emission reductions. Soil carbon stock changes were derived from about 200 studies, and the emission ranges for CH4 and N2O were derived using the DAYCENT and DNDC simulation models (IPCC, 2006; USEPA, 2006b; Smith et al., 2007b; Ogle et al., 2004, 2005). Table 8.5 presents the mitigation potentials in livestock (dairy cows, beef cattle, sheep, dairy buffalo and other buffalo) for reducing enteric methane emissions via improved feeding practices, specific agents and dietary additives, and longer term structural and management changes/animal breeding. These estimates were derived by Smith et al. (2007a) using a model similar to that described in US-EPA (2006b). Some mitigation measures operate predominantly on one GHG (e.g., dietary management of ruminants to reduce CH4 emissions) while others have impacts on more than one GHG (e.g., rice management). Moreover, practices may benefit more
Smith et al. (2007a) have recently collated per-area estimates of agricultural GHG mitigation options. This section draws largely from that study.
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Table 8.4: Annual mitigation potentials in each climate region for non-livestock mitigation options CO2 (tCO2/ha/yr) Climate zone Cool-dry
Activity Croplands Croplands Croplands Croplands Croplands Croplands Grasslands
Organic soils Degraded lands Manure/ biosolids Bioenergy Cool-moist Croplands Croplands Croplands Croplands Croplands Croplands Grasslands
Warm-dry
Organic soils Degraded lands Manure/ biosolids Bioenergy Croplands Croplands Croplands Croplands Croplands Croplands Grasslands
Warmmoist
Organic soils Degraded lands Manure/ biosolids Bioenergy Croplands Croplands Croplands Croplands Croplands Croplands Grasslands Organic soils Degraded lands Manure/ biosolids Bioenergy
Practice Agronomy Nutrient management Tillage and residue management Water management Set-aside and LUC Agro-forestry Grazing, fertilization, fire Restoration Restoration Application Soils only Agronomy Nutrient management tillage and residue management Water management Set-aside and LUC Agro-forestry Grazing, fertilization, fire Restoration Restoration Application
Mean estimate 0.29 0.26
CH4 (tCO2-eq/ha/yr)
Low
High
0.07 -0.22
0.51 0.73
Mean estimate 0.00 0.00
Low
High
0.00 0.00
0.00 0.00
N2O (tCO2-eq/ha/yr) Mean estimate 0.10 0.07
Low
High
0.00 0.01
0.20 0.32
All GHG (tCO2-eq/ha/yr) Mean estimate 0.39 0.33
Low
High
0.07 -0.21
0.71 1.05
0.15
-0.48
0.77
0.00
0.00
0.00
0.02
-0.04
0.09
0.17
-0.52
0.86
1.14
-0.55
2.82
0.00
0.00
0.00
0.00
0.00
0.00
1.14
-0.55
2.82
1.61 0.15 0.11
-0.07 -0.48 -0.55
3.30 0.77 0.77
0.02 0.00 0.02
0.00 0.00 0.01
0.00 0.00 0.02
2.30 0.02 0.00
0.00 -0.04 0.00
4.60 0.09 0.00
3.93 0.17 0.13
-0.07 -0.52 -0.54
7.90 0.86 0.79
36.67 3.45 1.54
3.67 -0.37 -3.19
69.67 7.26 6.27
-3.32 0.08 0.00
-0.05 0.04 0.00
-15.30 0.14 0.00
0.16 0.00 0.00
0.05 0.00 -0.17
0.28 0.00 1.30
33.51 3.53 1.54
3.67 -0.33 -3.36
54.65 7.40 7.57
0.15 0.88 0.55
-0.48 0.51 0.01
0.77 1.25 1.10
0.00 0.00 0.00
0.00 0.00 0.00
0.00 0.00 0.00
0.02 0.10 0.07
-0.04 0.00 0.01
0.09 0.20 0.32
0.17 0.98 0.62
-0.52 0.51 0.02
0.86 1.45 1.42
0.51
0.00
1.03
0.00
0.00
0.00
0.02
-0.04
0.09
0.53
-0.04
1.12
1.14
-0.55
2.82
0.00
0.00
0.00
0.00
0.00
0.00
1.14
-0.55
2.82
3.04 0.51 0.81
1.17 0.00 0.11
4.91 1.03 1.50
0.02 0.00 0.00
0.00 0.00 0.00
0.00 0.00 0.00
2.30 0.02 0.00
0.00 -0.04 0.00
4.60 0.09 0.00
5.36 0.53 0.80
1.17 -0.04 0.11
9.51 1.12 1.50
36.67 3.45 2.79
3.67 -0.37 -0.62
69.67 7.26 6.20
-3.32 1.00 0.00
-0.05 0.69 0.00
-15.30 1.25 0.00
0.16 0.00 0.00
0.05 0.00 -0.17
0.28 0.00 1.30
33.51 4.45 2.79
3.67 0.32 -0.79
54.65 8.51 7.50
0.51 0.29 0.26
0.00 0.07 -0.22
1.03 0.51 0.73
0.00 0.00 0.00
0.00 0.00 0.00
0.00 0.00 0.00
0.02 0.10 0.07
-0.04 0.00 0.01
0.09 0.20 0.32
0.53 0.39 0.33
-0.04 0.07 -0.21
1.12 0.71 1.05
0.33
-0.73
1.39
0.00
0.00
0.00
0.02
-0.04
0.09
0.35
-0.77
1.48
1.14
-0.55
2.82
0.00
0.00
0.00
0.00
0.00
0.00
1.14
-0.55
2.82
Soils only Agronomy Nutrient management Tillage and residue management Water management Set-aside and LUC Agro-forestry Grazing, fertilization, fire Restoration Restoration Application
1.61 0.33 0.11
-0.07 -0.73 -0.55
3.30 1.39 0.77
0.02 0.00 0.00
0.00 0.00 0.00
0.00 0.00 0.00
2.30 0.02 0.00
0.00 -0.04 0.00
4.60 0.09 0.00
3.93 0.35 0.11
-0.07 -0.77 -0.55
7.90 1.48 0.77
73.33 3.45 1.54
7.33 -0.37 -3.19
139.33 7.26 6.27
-3.32 0.00 0.00
-0.05 0.00 0.00
-15.30 0.00 0.00
0.16 0.00 0.00
0.05 0.00 -0.17
0.28 0.00 1.30
70.18 3.45 1.54
7.33 -0.37 -3.36
124.31 7.26 7.57
Soils only Agronomy
0.33 0.88
-0.73 0.51
1.39 1.25
0.00 0.00
0.00 0.00
0.00 0.00
0.02 0.10
-0.04 0.00
0.09 0.20
0.35 0.98
-0.77 0.51
1.48 1.45
Nutrient management Tillage and residue management Water management Set-aside and LUC Agro-forestry Grazing, fertilization, fire Restoration Restoration Application
0.55
0.01
1.10
0.00
0.00
0.00
0.07
0.01
0.32
0.62
0.02
1.42
0.70
-0.40
1.80
0.00
0.00
0.00
0.02
-0.04
0.09
0.72
-0.44
1.89
1.14
-0.55
2.82
0.00
0.00
0.00
0.00
0.00
0.00
1.14
-0.55
2.82
3.04 0.70 0.81
1.17 -0.40 0.11
4.91 1.80 1.50
0.02 0.00 0.00
0.00 0.00 0.00
0.00 0.00 0.00
2.30 0.02 0.00
0.00 -0.04 0.00
4.60 0.09 0.00
5.36 0.72 0.81
1.17 -0.44 0.11
9.51 1.89 1.50
73.33 3.45 2.79
7.33 -0.37 -0.62
139.33 7.26 6.20
-3.32 0.00 0.00
-0.05 0.00 0.00
-15.30 0.00 0.00
0.16 0.00 0.00
0.05 0.00 -0.17
0.28 0.00 1.30
70.18 3.45 2.79
7.33 -0.37 -0.79
124.31 7.26 7.50
Soils only 0.70 -0.40 1.80 0.00 0.00 0.00 0.02 -0.04 0.09 0.72 -0.44 1.89 Notes: The estimates represent average change in soil carbon stocks (CO2) or emissions of N2O and CH4 on a per hectare basis. Positive values represent CO2 uptake which increases the soil carbon stock, or a reduction in emissions of N2O and CH4. Estimates of soil carbon storage (CO2 mitigation) for all practices except management of organic soils were derived from about 200 studies (see IPCC, 2006, Grassland and Cropland Chapters of Volume IV, Annexes 5A and 6A) using a linear mixed-effect modelling approach, which is a standard linear regression technique with the inclusion of random effects due to dependencies in data from the same country, site and time series (Ogle et al., 2004, 2005; IPCC, 2006; Smith et al., 2007b). The studies were conducted in regions throughout the world, but temperate studies were more prevalent leading to smaller uncertainties than for estimates for warm tropical climates. Estimates represent annual soil carbon change rate for a 20-year time horizon in the top 30 cm of the soil. Soils under bio-energy crops and agro-forestry were assumed to derive their mitigation potential mainly from cessation of soil disturbance, and given the same estimates as no-till. Management of organic soils was based on emissions under drained conditions from IPCC guidelines (IPCC, 1997). Soil CH4 and N2O emission reduction potentials were derived as follows: a) for organic soils, N2O emissions were based on the median, low and high nutrient status organic soil N2O emission factors from the IPCC GPG LULUCF (IPCC, 2003) and CH4 emissions were based on low, high and median values from Le Mer and Roger (2001); b) N2O figures for nutrient management were derived using the DAYCENT simulation model, and include both direct emissions from nitrification/denitrification at the site, as well as indirect N2O emissions associated with volatilization and leaching/runoff of N that is converted into N2O following atmospheric deposition or in waterways, respectively (US-EPA, 2006b; assuming a N reduction to 80% of current application); c) N2O figures for tillage and residue management were derived using DAYCENT (US-EPA, 2006b; figures for no till); d) Rice figures were taken directly from US-EPA (2006b) so are not shown here. Low and high values represent the range of a 95% confidence interval. Table 8.4 has mean and uncertainty for change in soil C, N2O and CH4 emissions at the climate region scale, and are not intended for use in assessments at finer scales such as individual farms.
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Table 8.5: Technical reduction potential (proportion of an animal’s enteric methane production) for enteric methane emissions due to (i) improved feeding practices, (ii) specific agents and dietary additives and (iii) longer term structural/management change and animal breedinga Improved feeding practicesb
Longer term structural/management change and animal breedingd
Specific agents and dietary additivesc
Dairy buffalo
Nondairy buffalo
0.001
0.01
0.02
0.06
0.003
0.03
0.07
0.02
0.001
0.02
0.03
0.01
0.02
0.001
0.02
0.03
0.01
0.02
0.001
0.02
0.03
0.05
0.03
0.004
0.004
0.03
0.03
0.003
0.001
0.02
0.03
0.002
0.01
0.001
0.01
0.02
0.002
0.003
0.004
0.0002
0.004
0.006
0.0004
0.003
0.004
0.0002
0.004
0.006
0.0004
0.01
0.003
0.004
0.0002
0.004
0.006
0.0004
0.01
0.01
0.003
0.004
0.0002
0.004
0.006
0.0004
0.01
0.01
0.003
0.004
0.0002
0.004
0.006
0.0004
Dairy cows
Beef cattle
Sheep
Northern Europe
0.18
0.12
Southern. Europe
0.18
Western Europe
Nondairy buffalo
Dairy cows
Beef cattle
Sheep
0.04
0.08
0.04
0.12
0.04
0.08
0.18
0.12
0.04
Eastern. Europe
0.11
0.06
Russian Federation
0.10
Japan
0.17
South Asia
Dairy buffalo
Nondairy buffalo
Dairy cows
Beef cattle
Sheep
0.004
0.04
0.03
0.003
0.04
0.004
0.04
0.03
0.003
0.08
0.04
0.004
0.04
0.03
0.003
0.03
0.04
0.01
0.002
0.03
0.07
0.003
0.05
0.03
0.03
0.04
0.002
0.03
0.06
0.003
0.11
0.04
0.08
0.09
0.004
0.03
0.03
0.003
0.04
0.02
0.02
0.04
0.02
0.01
0.01
0.0005
0.01
0.002
0.01
0.01
East Asia
0.10
0.05
0.03
0.10
0.05
0.03
0.05
0.002
0.03
0.012
0.03
West Asia
0.06
0.03
0.02
0.06
0.03
0.01
0.02
0.001
0.01
0.004
0.01
Southeast Asia
0.06
0.03
0.02
0.06
0.03
0.01
0.02
0.001
0.01
0.004
Central Asia
0.06
0.03
0.02
0.06
0.03
0.01
0.02
0.001
0.01
0.004
Oceania
0.22
0.14
0.06
0.08
0.08
0.004
North America
0.16
0.11
0.04
0.11
0.09
South America
0.06
0.03
0.02
0.03
0.02
Central America
0.03
0.02
0.02
0.02
East Africa
0.01
0.01
0.01
West Africa
0.01
0.01
0.01
North Africa
0.01
0.01
South Africa
0.01
Middle Africa
0.01
AEZ regions
Dairy buffalo
Notes: a The proportional reduction due to application of each practice was estimated from reports in the scientific literature (see footnotes below). These estimates were adjusted for: (i) proportion of the animal’s life where the practice was applicable; (ii) technical adoption feasibility in a region, such as whether farmers have the necessary knowledge, equipment, extension services, etc. to apply the practice (average dairy cow milk production in each region over the period 2000-2004 was used as an index of the level of technical efficiency in the region, and was used to score a region’s technical adoption feasibility); (iii) proportion of animals in a region that the measure can be applied (i.e. if the measure is already being applied to some animals as in the case of bST use in North America, it is considered to be only applicable to the proportion of animals not currently receiving the product; (iv) Non-additivity of simultaneous application of multiple measures. There is evidence in the literature that some measures are not additive when applied simultaneously, such as the use of dietary oils and ionophores, but this is probably not the case with most measures. However, the model used (as described in Smith et al., 2007a) did account for the fact that once one measure is applied, the emissions base for the second measure is reduced, and so on, and a further 20% reduction in mitigation potential was incorporated to account for unknown non-additivity effects. Only measures considered feasible for a region were applied in that region (e.g., bST was not considered for European regions due to the ban on its use in the EU). It was assumed that total production of milk or meat was not affected by application of the practices, so that if a measure increased animal productivity, animal numbers were reduced in order to keep production constant. b Includes replacing roughage with concentrate (Blaxter & Claperton, 1965; Moe & Tyrrell, 1979; Johnson & Johnson, 1995; Yan et al., 2000; Mills et al., 2003; Beauchemin & McGinn, 2005; Lovett et al., 2006), improving forages/inclusion of legumes (Leng, 1991; McCrabb et al., 1998; Woodward et al., 2001; Waghorn et al., 2002; Pinares-Patiño et al., 2003; Alcock & Hegarty, 2006) and feeding extra dietary oil (Machmüller et al., 2000; Dohme et al., 2001; Machmüller et al., 2003, Lovett et al., 2003; McGinn et al., 2004; Beauchemin & McGinn, 2005; Jordan et al., 2006a; Jordan et al., 2006b; Jordan et al., 2006c). c Includes bST (Johnson et al., 1991; Bauman, 1992), growth hormones (McCrabb, 2001), ionophores (Benz & Johnson, 1982; Rumpler et al., 1986; Van Nevel & Demeyer, 1996; McGinn et al., 2004), propionate precursors (McGinn et al., 2004; Beauchemin & McGinn, 2005; Newbold et al., 2005; Wallace et al., 2006). d Includes lifetime management of beef cattle (Johnson et al., 2002; Lovett & O’Mara, 2002) and improved productivity through animal breeding (Ferris et al., 1999; Hansen, 2000; Robertson and Waghorn, 2002; Miglior et al., 2005). Source: adapted from Smith et al., 2007a.
than one gas (e.g., set-aside/headland management) while others involve a trade-off between gases (e.g., restoration of organic soils). The effectiveness of non-livestock mitigation options are variable across and within climate regions (see Table 8.4). Consequently, a practice that is highly effective in reducing emissions at one site may be less effective or even counterproductive elsewhere. Similarly, effectiveness of livestock options also varies regionally (Table 8.5). This means that there is no universally applicable list of mitigation practices, but that proposed practices will need to be evaluated for individual agricultural systems according to the specific climatic, edaphic, social settings, and historical land use and management.
Assessments can be conducted to evaluate the effectiveness of practices in specific areas, building on findings from the global scale assessment reported here. In addition, such assessments could address GHG emissions associated with energy use and other inputs (e.g., fuel, fertilizers, and pesticides) in a full life cycle analysis for the production system. The effectiveness of mitigation strategies also changes with time. Some practices, like those which elicit soil carbon gain, have diminishing effectiveness after several decades; others such as methods that reduce energy use may reduce emissions indefinitely. For example, Six et al. (2004) found a strong 513
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time dependency of emissions from no-till agriculture, in part because of changing influence of tillage on N2O emissions. 8.4.3
eq/yr) could be sequestered in global agricultural soils with a finite capacity saturating after 50 to100 years. In addition, SAR concluded that 300-1300 MtC (equivalent to about 11004800 MtCO2-eq/yr) from fossil fuels could be offset by using 10 to15% of agricultural land to grow energy crops; with crop residues potentially contributing 100-200 MtC (equivalent to about 400-700 MtCO2-eq/yr) to fossil fuel offsets if recovered and burned. Burning residues for bio-energy might increase N2O emissions but this effect was not quantified.
Global and regional estimates of agricultural GHG mitigation potential
8.4.3.1
Technical potential for GHG mitigation in agriculture
There have been numerous attempts to assess the technical potential for GHG mitigation in agriculture. Most of these have focused on soil carbon sequestration. Estimates in the IPCC Second Assessment Report (SAR; IPCC, 1996) suggested that 400-800 MtC/yr (equivalent to about 1400-2900 MtCO2-
A
SAR (IPCC, 1996) estimated that CH4 emissions from agriculture could be reduced by 15 to 56%, mainly through improved nutrition of ruminants and better management of paddy rice, and that improved management could reduce N2O
Gt CO2 eq/yr 8
all soil carbon
cropland soil carbon
7
soil carbon from desertification control
grassland soil carbon
all GHGs, all agriculture
6 5 4 3 2 1
Mt CO2 eq/yr 900 800 700
cropland soil carbon
soil carbon from land conversion
Canada all agriculture carbon all GHGs only
cropland soil carbon
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0
Figure 8.3: Global (A) and regional (B) estimates of technical mitigation potential by 2030 Note: Equivalent values for Smith et al. (2007a) are taken from Table 7 of Smith et al., 2007a.
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emissions by 9-26%. The document also stated that GHG mitigation techniques will not be adopted by land managers unless they improve profitability but some measures are adopted for reasons other than climate mitigation. Options that both reduce GHG emissions and increase productivity are more likely to be adopted than those which only reduce emissions.
eq/yr by Smith et al. (2007a) if considering no economic or other barriers. Economic potentials are considerably lower (see Section 8.4.3.2). Figure 8.3 presents global and regional estimates of agricultural mitigation potential. Of the technical potentials estimated by Smith et al. (2007a), about 89% is from soil carbon sequestration, about 9% from mitigation of methane and about 2% from mitigation of soil N2O emissions (Figure 8.4). The total mitigation potential per region is presented in Figure 8.5.
Of published estimates of technical potential, only Caldeira et al. (2004) and Smith et al. (2007a) provide global estimates considering all GHGs together, and Boehm et al. (2004) consider all GHGs for Canada only for 2008. Smith et al. (2007a) used per-area or per-animal estimates of mitigation potential for each GHG and multiplied this by the area available for that practice in each region. It was not necessary to use baseline emissions in calculating mitigation potential. US-EPA (2006b) estimated baseline emissions for 2020 for non-CO2 GHGs as 7250 MtCO2-eq in 2020 (see Chapter 11; Table 11.4). NonCO2 GHG emissions in agriculture are projected to increase by about 13% from 2000 to 2010 and by 13% from 2010 to 2020 (US-EPA, 2006b). Assuming a similar rate of increase as in the period from 2000 to 2020, global agricultural non-CO2 GHG emissions would be around 8200 MtCO2-eq in 2030.
The uncertainty in the estimates of the technical potential is given in Figure 8.6, which shows one standard deviation either side of the mean estimate (box), and the 95% confidence interval about the mean (line). The range of the standard deviation, and the 95% confidence interval about the mean of 5800 MtCO2-eq/ yr, are 3000-8700, and 300-11400 MtCO2-eq/yr, respectively, and are largely determined by uncertainty in the per-area estimate for the mitigation measure. For soil carbon sequestration (89% of the total potential), this arises from the mixed linear effects model used to derive the mitigation potentials. The most appropriate mitigation response will vary among regions, and different portfolios of strategies will be developed in different regions, and in countries within a region.
The global technical potential for mitigation options in agriculture by 2030, considering all gases, was estimated to be ~4500 by Caldeira et al. (2004) and ~5500-6000 MtCO2-
Mt CO2-eq/yr
1800
N2O
1600
CH4 1400
CO2
1200 1000 800 600 400 200
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Figure 8.4: Global technical mitigation potential by 2030 of each agricultural management practice showing the impacts of each practice on each GHG. Note: based on the B2 scenario though the pattern is similar for all SRES scenarios. Source: Drawn from data in Smith et al., 2007a.
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Figure 8.5: Total technical mitigation potentials (all practices, all GHGs: MtCO2-eq/yr) for each region by 2030, showing mean estimates. Note: based on the B2 scenario though the pattern is similar for all SRES scenarios. Source: Drawn from data in Smith et al., 2007a.
8.4.3.2
Economic potential for GHG mitigation in agriculture
US-EPA (2006b) provided estimates of the agricultural mitigation potential (global and regional) at various assumed
1800
carbon prices, for N2O and CH4, but not for soil carbon sequestration. Manne & Richels (2004) estimated the economic mitigation potential (at 27 US$/tCO2-eq) for soil carbon sequestration only.
Mt CO2-eq/yr
1600 1400 1200 1000 800 600 400 200
s ut ia h As ia st R er us n si Af an Fe rica de ra N tio or th n A W m es e ric te rn a Eu W r op es e te rn Af ric C en a N tra or lA th er si a n Eu ro M pe id dl e Ea Af st ric er a n Eu ro pe O So c ea ut he ni a rn C E en ur op tra e lA m N er or ic th a er n A fri W ca es te rn So As ut ia he rn Af ric a C ar rib ea n Ja pa n Po ly ne si a
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Region Figure 8.6: Total technical mitigation potentials (all practices, all GHGs) for each region by 2030 Note: Boxes show one standard deviation above and below the mean estimate for per-area mitigation potential, and the bars show the 95% confidence interval about the mean. Based on the B2 scenario, although the pattern is similar for all SRES scenarios. Source: Drawn from data in Smith et al., 2007a.
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Table 8.6: Global agricultural mitigation potential in 2030 from top-down models Carbon price US$/tCO2-eq 0-20 20-50 50-100 >100
CH4 0-1116 348-1750 388 733
Mitigation (MtCO2-eq/yr) N2O 89-402 116-1169 217 475
Number of scenarios CH4+N2O 267-1518 643-1866 604 1208
6 6 1 1
Note: From Chapter 3, Sections 3.3.5 and 3.6.2. Source: Data assembled from USCCSP, 2006; Rose et al., 2007; Fawcett and Sands, 2006; Smith and Wigley, 2006; Fujino et al., 2006; and Kemfert et al., 2006.
In the IPCC Third Assessment Report (TAR; IPCC, 2001b), estimates of agricultural mitigation potential by 2020 were 350750 MtC/yr (~1300-2750 MtCO2/yr). The range was mainly caused by large uncertainties about CH4, N2O, and soil-related CO2 emissions. Most reductions will cost between 0 and 100 US$/tC-eq (~0-27 US$/tCO2-eq) with limited opportunities for negative net direct cost options. The analysis of agriculture included only conservation tillage, soil carbon sequestration, nitrogen fertilizer management, enteric methane reduction and rice paddy irrigation and fertilizers. The estimate for global mitigation potential was not broken down by region or practice. Smith et al. (2007a) estimated the GHG mitigation potential in agriculture for all GHGs, for four IPCC SRES scenarios, at a range of carbon prices, globally and for all world regions. Using methods similar to McCarl and Schneider (2001), Smith et al. (2007a) used marginal abatement cost (MAC) curves given in US-EPA (2006b) for either region-specific MACs where available for a given practice and region, or global MACs where these were unavailable from US-EPA (2006b). Recent bottom-up estimates of agricultural mitigation potential of CH4 and N2O from US-EPA (2006b) and DeAngelo et al. (2006) have allowed inclusion of agricultural abatement into top-down global modelling of long-term climate stabilization scenario pathways. In the top-down framework, a dynamic cost-effective portfolio of abatement strategies is identified. The portfolio includes the least-cost combination of mitigation strategies from across all sectors of the economy, including agriculture. Initial implementations of agricultural abatement into top-down models have employed a variety of alternative approaches resulting in different decision modelling of agricultural abatement (Rose et al., 2007). Currently, only non-CO2 GHG crop (soil and paddy rice) and livestock (enteric and manure) abatement options are considered by top-down models. In addition, some models also consider emissions from burning of agricultural residues and waste, and fossil fuel combustion CO2 emissions. Top-down estimates of global CH4 and N2O mitigation potential, expressed in CO2 equivalents, are given in Table 8.6 and Figure 8.7. Comparing mitigation estimates from top-down and bottomup modelling is not straightforward. Bottom-up mitigation responses are typically constrained to input management (e.g.,
fertilizer quantity, livestock feed type) and cost estimates are partial equilibrium in that input and output market prices are fixed as can be key input quantities such as acreage or production. Top-down mitigation responses include more generic input management responses and changes in output (e.g., shifts from cropland to forest) as well as changes in market prices (e.g., decreases in land prices with increasing production costs due to a carbon tax). Global estimates of economic mitigation potential from different studies at different assumed carbon prices are presented in Figure 8.8. The top-down 2030 carbon prices, as well as the agricultural mitigation response, reflect the confluence of multiple forces, including differences in implementation of agricultural emissions and mitigation, as well as the stabilization target used, the magnitude of baseline emissions, baseline energy technology options, the eligible set of mitigation options, and the solution algorithm. As a result, the opportunity cost of agricultural mitigation in 2030 is very different across scenarios (i.e., model/baseline/mitigation option combinations). As illustrated by the connecting lines in Figure 8.7, agricultural abatement Mt CO2-eq/yr
2000
4-5 W/m2 (590-710 ppm CO2-eq concentration)
1800 1600
3.25-4 W/m2 (510-590 ppm CO2-eq concentration)
1400
< 3.25 W/m2 (< 510 ppm CO2-eq concentration)
1200 1000 800 600 400 200 0 0
20
40
60 80 US$/tCO2-eq
100
120
140
Figure 8.7: Global agricultural mitigation potential in 2030 from top-down models by carbon price and stabilisation target Note: Dashed lines connect results from scenarios where tighter stabilization targets were modelled with the same model and identical baseline characterization and mitigation technologies. From Chapter 3, Sections 3.3.5 and 3.6.2. Source: Data assembled from USCCSP, 2006; Rose et al., 2007; Fawcett and Sands, 2006; Smith and Wigley, 2006; Fujino et al., 2006; Kemfert et al., 2006.
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Mt CO2-eq/yr all GHG
3000
N2O and CH4 only
CO2 only
@ 27 US$/ @ 27 US$/ tCO2-eq tCO2-eq
@ 20 US$/ tCO2-eq
@ 50 US$/ tCO2-eq
soil N2O only @ 100 US$/ tCO2-eq
@ 20 US$/ tCO2-eq
rice all GHG
@ 50 US$/ @ 20 US$/ tCO2-eq tCO2-eq
livestock CH4 only
@ 50 US$/ @ 100 US$/ @ 20 US$/ tCO2-eq tCO2-eq tCO2-eq
@ 50 US$/ tCO2-eq
2500
2000
1500
1000
500
20
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0
Figure 8.8: Global economic potentials for agricultural mitigation arising from various practices shown for comparable carbon prices at 2030. Notes: US-EPA (2006b) figures are for 2020 rather than 2030. Values for top-down models are taken from ranges given in Figure 8.7.
is projected to increase with the tightness of the stabilization target. On-going model development in top-down land-use modelling is expected to yield more refined characterizations of agricultural alternatives and mitigation potential in the future.
tCO2-eq., respectively shown for OECD versus EIT versus non-OECD/EIT (Table 8.7). The change in global mitigation potential with increasing carbon price for each practice is shown in Figure 8.9.
Smith et al. (2007a) estimated global economic mitigation potentials for 2030 of 1500-1600, 2500-2700, and 4000-4300 MtCO2-eq/yr at carbon prices of up to 20, 50 and 100 US$/
Table 8.7: Estimates of the global agricultural economic GHG mitigation potential (MtCO2-eq/yr) by 2030 under different assumed prices of CO2-equivalents Price of CO2-eq (US$/tCO2-eq) SRES Scenario B1
Up to 20
Up to 50
Up to 100
OECD
310 (60-450)
510 (290-740)
810 (440-1180)
EIT
150 (30-220)
250 (140-370)
410 (220-590)
Non-OECD/EIT A1b
1080 (210-1560)
1780 (1000-2580)
2830 (1540-4120)
OECD
320 (60-460)
520 (290-760)
840 (450-1230)
EIT
160 (30-230)
260 (150-380)
410 (220-610)
1110 (210-1610)
1820 (1020-2660)
2930 (1570-4290)
Non-OECD/EIT B2
OECD
330 (60-470)
540 (300-780)
870 (460-1280)
EIT
160 (30-240)
270 (150-390)
440 (230-640)
Non-OECD/EIT A2
1140 (210-1660)
1880 (1040-2740)
3050 (1610-4480)
OECD
330 (60-480)
540 (300-790)
870 (460-1280)
EIT
165 (30-240)
270 (150-400)
440 (230-640)
1150 (210-1670)
1890 (1050-2760)
3050 (1620-4480)
Non-OECD/EIT
Note: Figures in brackets show one standard deviation about the mean estimate.
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1400
Mt CO2-eq/yr up to 20 US$/tCO2-eq. up to 50 US$/tCO2-eq. up to 100 US$/tCO2-eq.
1200 1000 800 600 400 200
na ma ge nu me re nt ma
se
t-a si ag de, ro LU for C es & try
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Mitigation measure Figure 8.9: Economic potential for GHG agricultural mitigation by 2030 at a range of prices of CO2-eq Note: Based on B2 scenario, although the pattern is similar for all SRES scenarios. Source: Drawn from data in Smith et al., 2007a.
8.4.4
Bioenergy feed stocks from agriculture
Bioenergy to replace fossil fuels can be generated from agricultural feedstocks, including by-products of agricultural production, and dedicated energy crops. 8.4.4.1
Residues from agriculture
The energy production and GHG mitigation potentials depend on yield/product ratios, and the total agricultural land area as well as type of production system. Less intensive management systems require re-use of residues for maintaining soil fertility. Intensively managed systems allow for higher utilization rates of residues, but also usually deploy crops with higher crop-toresidue ratios. Estimates of energy production potential from agricultural residues vary between 15 and 70 EJ/yr. The latter figure is based on the regional production of food (in 2003) multiplied by harvesting or processing factors, and assumed recoverability factors. These figures do not subtract the potential competing uses of agricultural residues which, as indicated by (Junginger et al., 2001), can reduce significantly the net availability of agricultural residues for energy or materials. In addition, the expected future availability of residues from agriculture varies widely among studies. Dried dung can also be used as an energy feedstock. The total estimated contribution could be 5 to 55 EJ/ yr worldwide, with the range defined by current global use at
the low end, and technical potential at the high end. Utilization in the longer term is uncertain because dung is considered to be a “poor man’s fuel”. Organic wastes and residues together could supply 20125 EJ/yr by 2050, with organic wastes making a significant contribution. 8.4.4.2
Dedicated energy crops
The energy production and GHG mitigation potentials of dedicated energy crops depends on availability of land, which must also meet demands for food as well as for nature protection, sustainable management of soils and water reserves, and other sustainability criteria. Because future biomass resource availability for energy and materials depends on these and other factors, an accurate estimate is difficult to obtain. Berndes et al. (2003) in reviewing 17 studies of future biomass availability found no complete integrated assessment and scenario studies. Various studies have arrived at differing figures for the potential contribution of biomass to future global energy supplies, ranging from below 100 EJ/yr to above 400 EJ/ yr in 2050. Smeets et al. (2007) indicate that ultimate technical potential for energy cropping on current agricultural land, with projected technological progress in agriculture and livestock, could deliver over 800 EJ/yr without jeopardizing the world’s food supply. In Hoogwijk et al. (2005) and Hoogwijk (2004), the IMAGE 2.2 model was used to analyse biomass production 519
Agriculture
potentials for different SRES scenarios. Biomass production on abandoned agricultural land is calculated at 129 EJ (A2) up to 411 EJ (A1) for 2050 and possibly increasing after that timeframe. 273 EJ (for A1) – 156 EJ (for A2) may be available below US$ 2/GJ production costs. A recent study (Sims et al., 2006) which used lower per-area yield assumptions and bioenergy crop areas projected by the IMAGE 2.2 model suggested more modest potentials (22 EJ/yr) by 2025. Based on assessment of other studies, Hoogwijk et al. (2003), indicated that marginal and degraded lands (including a land surface of 1.7 Gha worldwide) could, be it with lower productivities and higher production costs, contribute another 60-150 EJ. Differences among studies are largely attributable to uncertainty in land availability, energy crop yields, and assumptions on changes in agricultural efficiency. Those with the largest projected potential assume that not only degraded/ surplus land are used, but also land currently used for food production (including pasture land, as did Smeets et al., 2007). Converting the potential biomass production into a mitigation potential is not straightforward. First, the mitigation potential is determined by the lowest supply and demand potentials, so without the full picture (see Chapter 11) no estimate can be made. Second, any potential from bioenergy use will be counted towards the potential of the sectors where bioenergy is used (mainly energy supply and transport). Third, the proportion of the agricultural biomass supply compared to that from the waste or forestry sector cannot be specified due to lack of information on cost curves. Top-down integrated assessment models can give an estimate of the cost competitiveness of bioenergy mitigation options relative to one another and to other mitigation options in achieving specific climate goals. By taking into account the various bioenergy supplies and demands, these models can give estimates of the combined contribution of the agriculture, waste, and forestry sectors to bioenergy mitigation potential. For achieving long-term climate stabilization targets, the competitive cost-effective mitigation potential of biomass energy (primarily from agriculture) in 2030 is estimated to be 70 to 1260 MtCO2-eq/yr (0-13 EJ/yr) at up to 20 US$/t CO2-eq, and 560-2320 MtCO2-eq/yr (0-21 EJ/yr) at up to 50 US$/tCO2eq (Rose et al., 2007, USCCSP, 2006). There are no estimates for the additional potential from top down models at carbon prices up to 100 US$/tCO2-eq, but the estimate for prices above 100 US$/tCO2-eq is 2720 MtCO2-eq/yr (20-45 EJ/yr). This is of the same order of magnitude as the estimate from a synthesis of supply and demand presented in Chapter 11, Section 11.3.1.4. The mitigation potentials estimated by topdown models represent mitigation of 5-80%, and 20-90% of all other agricultural mitigation measures combined, at carbon prices of up to 20, and up to 50 US$/tCO2-eq, respectively.
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8.4.5
Potential implications of mitigation options for sustainable development
There are various potential impacts of agricultural GHG mitigation on sustainable development. The impacts of mitigation activities in agriculture, on the constituents and determinants of sustainable development are set out in Table 8.8. Broadly, three constituents of sustainable development have been envisioned as the critical minimum: social, economic, and environmental factors. Table 8.8 presents the degree and direction of the likely impact of the mitigation options. The exact magnitude of the effect, however, depends on the scale and intensity of the mitigation measures, and the sectors and policy arena in which they are undertaken. Agriculture contributes 4% of global GDP (World Bank, 2003) and provides employment to 1.3 billion people (Dean, 2000). It is a critical sector of the world economy, but uses more water than any other sector. In low-income countries, agriculture uses 87% of total extracted water, while this figure is 74% in middle-income countries and 30% in high-income countries (World Bank, 2003). There are currently 276 Mha of irrigated croplands (FAOSTAT, 2006), a five-fold increase since the beginning of the 20th century. With irrigation increasing, water management is a serious issue. Through proper institutions and effective functioning of markets, water management can be implemented with favourable outcomes for both environmental and economic goals. There is a greater need for policy coherence and innovative responses creating a situation where users are asked to pay the full economic costs of the water. This has special relevance for developing countries. Removal of subsidies in the electricity and water sectors might lead to effective water use in agriculture, through adaptation of appropriate irrigation technology, such as drip irrigation in place of tube well irrigation. Agriculture contributes nearly half of the CH4 and N2O emissions (Bhatia et al., 2004) and rice, nutrient, water and tillage management can help to mitigate these GHGs. By careful drainage and effective institutional support, irrigation costs for farmers can also be reduced, thereby improving economic aspects of sustainable development (Rao, 1994). An appropriate mix of rice cultivation with livestock, known as integrated annual crop-animal systems and traditionally found in West Africa, India and Indonesia and Vietnam, can enhance net income, improve cultivated agro-ecosystems, and enhance human well-being (Millennium Ecosystem Assessment, 2005). Such combinations of livestock and cropping, especially for rice, can improve income generation, even in semi-arid and arid areas of the world. Groundwater quality may be enhanced and the loss of biodiversity can be influenced by the choice of fertilizer used and use of more targeted pesticides. Further, greater demand for farmyard manure would create income for the animal husbandry sector where usually the poor are engaged. Various country
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Table 8.8: Potential sustainable development consequences of mitigation options Activity category Croplands – agronomy Croplands – nutrient management Croplands – tillage/residues Croplands – water management Croplands – rice management Croplands – set-aside & LUC Croplands – agro-forestry Grasslands – grazing, nutrients, fire Organic soils – restoration Degraded soils – restoration Biosolid applications Bioenergy Livestock – feeding Livestock – additives Livestock – breeding Manure management
Social
Sustainable development Economic
Environmental
? ? ? + + ? + + ? + + + -/? -/? -/? ?
+ + ? + + ? + ? + ? + n/d n/d n/d
+ + + + + + + + + + +/+/? n/d n/d n/d
Notes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 14 15
Notes: + denotes beneficial impact on component of SD - denotes negative impact ? denotes uncertain impact n/d denotes no data 1 Improved yields would mean better economic returns and less land required for new cropland. Societal impact uncertain - impact could be positive but could negatively affect traditional practices. 2 Improved yields would mean better economic returns and less land required for new cropland. Societal impact uncertain - impact could be positive but could negatively affect traditional practices. 3 Improves soil fertility may not increase yield so societal and economic impacts uncertain. 4 All efficiency improvements are positive for sustainability goals and should yield economic benefits even if costs of irrigation are borne by the farmer. 5 Improved yields would mean better economic returns and less land required for new cropland. Societal impacts likely to benign or positive as no large-scale change to traditional practices. 6 Improve soil fertility but less land available for production; potential negative impact on economic returns. 7 Likely environmental benefits, less travel required for fuelwood; positive societal benefits; economic impact uncertain. 8 Improved production would mean better economic returns and less land required for grazing; lower degradation. Societal effects likely to be positive. 9 Organic soil restoration has a host of biodiversity/environmental co-benefits but opportunity cost of crop production lost from this land; economic impact depends upon whether farmers receive payment for the GHG emission reduction. 10 Restoration of degraded lands will provide higher yields and economic returns, less new cropland and provide societal benefits via production stability. 11 Likely environmental benefits though some negative impacts possible (e.g., water pollution) but, depending on the bio-solid system implemented, could increase costs. 12 Bio-energy crops could yield environmental co-benefits or could lead to loss of bio-diversity (depending on the land use they replace). Economic impact uncertain. Social benefits could arise from diversified income stream. 13 Negative/uncertain societal impacts as these practices may not be acceptable due to prevailing cultural practices especially in developing countries. Could improve production and economic returns. 14 Negative/uncertain societal impacts as these practices may not be acceptable due to prevailing cultural practices especially in developing countries. No data (n/d) on economic or environmental impacts. 15 Uncertain societal impacts. No data (n/d) on economic or environmental impacts.
strategy papers on The Millennium Development Goal (MDG) clearly recommend encouragement to animal husbandry (e.g., World Bank, 2005). This is intended to enhance livelihoods and create greater employment. Better nutrient management can also improve environmental sustainability. Controlling overgrazing through pasture improvement has a favourable impact on livestock productivity (greater income from the same number of livestock) and slows or halts desertification (environmental aspect). It also provides social security to the poorest people during extreme events such as drought (especially in Sub-Saharan Africa). One effective strategy to control overgrazing is the prohibition of free
grazing, as was done in China (Rao, 1994) but approaches in other regions need to take into account cultural and institutional contexts. Dryland and desert areas have the highest number of poor people (Millennium Ecosystem Assessment, 2005) and measures to halt overgrazing, coupled with improved livelihood options (e.g., fisheries in Syria , Israel and other central Asian countries), can help reduce poverty and achieve sustainability goals. Land cover and tillage management could encourage favourable impacts on environmental goals. A mix of horticulture with optimal crop rotations would promote carbon sequestration and could also improve agro-ecosystem function. 521
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Societal well-being would also be enhanced by providing water and enhanced productivity. While the environmental benefits of tillage/residue management are clear, other impacts are less certain. Land restoration will have positive environmental impacts, but conversion of floodplains and wetlands to agriculture could hamper ecological function (reduced water recharge, bioremediation, nutrient cycling, etc.) and therefore, could have an adverse impact on sustainable development goals (Kumar, 2001). The other mitigation measures listed in Table 8.8 are context- and location-specific in their influence on sustainable development constituents. Appropriate adoption of mitigation measures is likely in many cases to help achieve environmental goals, but farmers may incur additional costs, reducing their returns and income. This trade-off would be most visible in the short term, but in the long term, synergy amongst the constituents of sustainable development would emerge through improved natural capital. Trade-offs between economic and environmental aspects of sustainable development might become less important if the environmental gains were better acknowledged, quantified, and incorporated in the decisionmaking framework. Large-scale production of modern bioenergy crops, partly for export, could generate income and employment for rural regions of world. Nevertheless, these benefits will not necessarily flow to the rural populations that need them most. The net impacts for a region as a whole, including possible changes and improvements in agricultural production methods should be considered when developing biomass and bioenergy production capacity. Although experience around the globe (e.g., Brazil, India biofuels) shows that major socioeconomic benefits can be achieved, new bioenergy production schemes could benefit from the involvement of the regional stakeholders, particularly the farmers. Experience with such schemes needs to be built around the globe.
Chapter 8
increased nitrous oxide emissions). In many cases, actions taken for reasons unrelated to either mitigation or adaptation (see Sections 8.6 and 8.7) may have considerable consequences for either or both(e.g., deforestation for agriculture or other purposes results in carbon loss as well as loss of ecosystems and resilience of local populations). Adaptation to climate change in the agricultural sector is detailed in (IPCC, 2007; Chapter 5). For mitigation, variables such as growth rates for bioenergy feedstocks, the size of livestock herds, and rates of carbon sequestration in agricultural lands are affected by climate change (Paustian et al., 2004). The extent depends on the sign and magnitude of changes in temperature, soil moisture, and atmospheric CO2 concentration, which vary regionally (Christensen et al., 2007). All of these factors will alter the mitigation potential; some positively and some negatively. For example: (a) lower growth rates in bioenergy feedstocks will lead to larger emissions from hauling and increased cost; (b) lower livestock growth rates would possibly increase herd size and consequent emissions from manure and enteric fermentation; and (c) increased microbial decomposition under higher temperatures will lower soil carbon sequestration potential. Interactions also occur with adaptation. Butt et al. (2006) and Reilly et al. (2001) found that modified crop mix, land use, and irrigation are all potential adaptations to warmer climates. All would alter the mitigation potential. Some of the key vulnerabilities of agricultural mitigation strategies to climate change, and the implications of adaptation on GHG emissions from agriculture are summarized in Table 8.9.
8.6 Effectiveness of, and experience with, climate policies; potentials, barriers and opportunities/implementation issues
8.6.1
8.5 Interactions of mitigation options with adaptation and vulnerability As discussed in Chapters 3, 11 and 12, mitigation, climate change impacts, and adaptation will occur simultaneously and interactively. Mitigation-driven actions in agriculture could have (a) positive adaptation consequences (e.g., carbon sequestration projects with positive drought preparedness aspects) or (b) negative adaptation consequences (e.g., if heavy dependence on biomass energy increases the sensitivity of energy supply to climatic extremes; see Chapter 12, Subsection 12.1.4). Adaptation-driven actions also may have both (a) positive consequences for mitigation (e.g., residue return to fields to improve water holding capacity will also sequester carbon); and (b) negative consequences for mitigation (e.g., increasing use of nitrogen fertilizer to overcome falling yield leading to 522
Impact of climate policies
Many recent studies have shown that actual levels of GHG mitigation are far below the technical potential for these measures. The gap between technical potential and realized GHG mitigation occurs due to costs and other barriers to implementation (Smith, 2004b). Globally and for Europe, Cannell (2003) suggested that, for carbon sequestration and bioenergy-derived fossil fuel offsets, the realistically achievable potential (potential estimated to take account of all barriers) was ~20% of the technical potential. Similar figures were derived by Freibauer et al. (2004) and the European Climate Change Programme (2001) for agricultural carbon sequestration in Europe. Smith et al. (2005a) showed recently that carbon sequestration in Europe is likely to be negligible by the first Commitment Period of the Kyoto Protocol (2008-2012), despite the significant technical potential (e.g.,
Only weakly sensitive to climate change, except in cases where the entire cropping enterprise becomes unviable. Sensitive to climate change. Higher temperatures could lower soil carbon sequestration potential. Warmer, wetter climates can increase risk of crop pests and diseases associated with reduced till practices. Irrigation is susceptible to climate changes that reduce the availability of water for irrigation or increases crop water demand.
Cropland management – agronomy
Cropland management – nutrient management
Cropland management – tillage/residue management
Bioenergy – energy crops, solid, liquid, biogas, residues
Livestock - improved feeding practices, specific agents and dietary additives, longer term structural and management changes and animal breeding Manure/biosolid management
Restoration of degraded lands
Management of agricultural organic soils
Grazing land management/pasture improvement
Cropland management – agro-forestry
Controlled waste digestion generally positively affected by moderately rising temperatures. Where GHGs are not trapped, higher temperatures could hamper management. Particular bioenergy crops potentially sensitive to climate change, either positively or negatively. Areas devoted to bioenergy could be under increasing competition with the needs for food agriculture or biodiversity conservation under changing climate.
Large changes in climate could make certain forms of agro-forestry unviable in particular situations. Fire management can be impacted negatively or positively by climate change depending on ecosystem and sign of climate change. Extreme drying or warming could make marginal grazing lands unviable. Wetter conditions will promote conversion of grazing lands to crops. The mitigation measure is sensitive to increases in temperature or decreases in moisture, both of which would decrease the carbon sequestration potential. The sustainability of restored lands could be vulnerable to increased temperature and/or decreased soil moisture. Weakly vulnerable to climate change except if it leads to the loss of viability of livestock enterprises in marginal areas or increased cost (or decreased availability) of feed inputs.
Cropland management – rice management Vulnerable to climate-change-induced changes in water availability. Low CH4 emitting cultivars may be susceptible to changes in temperature beyond their tolerance limits. Cropland management – set-aside and Set-asides may be needed to offset loss of productivity on other land-use change lands.
Cropland management – water management
Vulnerability of the mitigation option to climate change Vulnerable to decreased rainfall, and in cases near the limit of their climate niche, to higher temperatures.
Agricultural mitigation strategies
Generally, results in net CO2 uptake on land (apart from the fossil-fuel substitution). N2O emissions would increase if N turnover rates were greater than under previous land uses. Possible positive and negative impacts on net GHG emissions at various stages of the energy chain (cultivation, harvesting, transport, conversion) must be managed.
If used as a nutrient source on pasture can increase CO2 uptake and carbon storage.
Some trade-offs between CO2 uptake and CH4 emissions can be expected if the soils become wetter as a result of the adaptation management. Energy used to replant, or fertilizer used to increase establishment, success could lead to small additional GHG emissions No general adaptation strategies. Specific strategies may have minor impacts on GHG emissions, for example, transport of feed supplements from distant locations could lead to increased net GHG emissions.
Adaptation is either to try to keep production high on non-set-aside land, which could increase GHG emissions, or return some set-asides to production. Increases in GHGs are in both cases fairly small, and less than the case of not having set-asides in the first place. They could be further mitigated by applying low GHG emitting practices in all cases. Adaptation of practices and species used to less favourable climates could lead to some loss of CO2 uptake potential. Increased fire protection activities can increase GHGs emissions by a small amount, thus reducing the net benefit obtained from reducing fire extent and frequency.
Possible increase in energy-related GHG emissions if greater pumping distances or volumes are required. Adoption of more water-use efficient practices will generally lower GHG emissions. Adaptation strategies are limited and not expected to have large GHG consequences.
NO2 emissions would increase if fertilizer use increased, or if more legumes were planted in response to climate-induced production declines. No significant adaptation to effects of climate change possible beyond tailoring of practices to ambient conditions. Therefore, additional GHGs not expected. Adaptation not anticipated to have a significant GHG effect.
Implication for GHG emissions of adaptation actions
Table 8.9: Some of the key vulnerabilities of agricultural mitigation strategies to climate change and the implications of adaptation on GHG emissions from agriculture
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Smith et al., 2000; Freibauer et al., 2004; Smith, 2004a). The estimates of global economic mitigation potential in 2030 at different costs reported in Smith et al. (2007a) were 28, 45 and 73% of technical potential at up to 20, 50 and 100 US$/tCO2eq, respectively. In Europe, there is little evidence that climate policy is affecting GHG emissions from agriculture (see Smith et al., 2005a), with most emission reduction occurring through nonclimate policy (see Section 8.7; Freibauer et al., 2004). Some countries have agricultural policies designed to reduce GHG emissions (e.g., Belgium), but most do not (Smith et al., 2005a). The European Climate Change Programme (2001) recommended improvement of fertilizer application, set-aside, and reduction of livestock methane emissions (mainly through biogas production) as being the most cost-effective GHG mitigation options for European agriculture. In North America, the US Global Climate Change Initiative aims to reduce GHG intensity by 18% by 2012. Agricultural sector activities include manure management, reduced tillage, grass plantings, and afforestation of agricultural land. In Canada, agriculture contributes about 10% to national emissions, so mitigation (removals and emission reductions) is considered to be an important contribution to reducing emissions (and at the same time to reduce risk to air, water and soil quality). Various programmes (e.g., AAFC GHG Mitigation programme) encourage voluntary adoption of mitigation practices on farms. In Oceania, vegetation management policies in Australia have assisted in progressively restricting emissions from landuse change (mainly land clearing for agriculture) to about 60% of 1990 levels. Complementary policies that aim to foster establishment of both commercial and non-commercial forestry and agro-forestry are resulting in significant afforestation of agricultural land in both Australia and New Zealand. Research is being supported to develop cost-effective GHG abatement technologies for livestock (including dietary manipulation and other methods of reducing enteric methane emissions, as well as manure management), agricultural soils (including nutrient and soil management strategies), savannas, and planted forests. The Greenhouse Challenge Plus programme and other partnership initiatives between the Government and industry are facilitating the integration of GHG abatement measures into agricultural management systems. In Latin America and the Caribbean, climate change mitigation is still not considered in mainstream policy. Most countries have devoted efforts to capacity building for complying with obligations under the UNFCCC, and a few have prepared National Strategy Studies for Kyoto Protocol’s Clean Development Mechanism (CDM). Carbon sequestration in agricultural soils has the highest mitigation potential in the region, and its exclusion from the CDM has hindered wider adoption of pertinent practices (e.g., zero tillage).
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In Asia, China has policies that reduce GHG emissions, but these were implemented for reasons other than climate policy. These are discussed further in Section 8.7. Currently, there are no policies specifically aimed at reducing GHG emissions. Japan has a number of policies such as Biomass Nippon Strategy, which promotes the utilization of biomass as an alternative energy source, and Environment-Conserving Agriculture, which promotes energy-efficient agricultural machinery, reduction in use of fertilizer, and appropriate management of livestock waste, etc. In Africa, the impacts of climate policy on agricultural emissions are small. There are no approved CDM projects in Africa related to the reduction of agricultural GHG emissions per se. Several projects are under investigation in relation to the restoration of agriculturally-degraded lands, carbon sequestration potential of agro-forestry, and reduction in sugarcane burning. Many countries in Africa have prepared National Strategy Studies for the CDM in complying with obligations under UNFCCC. The main obstacles to implementation of CDM projects in Africa, however, are lack of financial resources, qualified personnel, and the complexity of the CDM. Agricultural GHG offsets can be encouraged by marketbased trading schemes. Offset trading, or trading of credits, allows farmers to obtain credits for reducing their GHG emission reductions. The primary agricultural project types include CH4 capture and destruction, and soil carbon sequestration. Although not included in current projects, measures to reduce N2O emissions could be included in the future. The vast majority of agricultural projects have focused on CH4 reduction from livestock wastes in North America (Canada, Mexico and the United States), South America (Brazil), China, and Eastern Europe. Most of these projects have resulted in the production of Certified Emission Reductions (CERs) from the CDM. Credits are bought and sold through the use of offset aggregators, brokers, and traders. Although the CDM does not currently support soil carbon sequestration projects, emerging markets in Canada and the United States are supporting offset trading from soil carbon sequestration. In Canada, farm groups such as the Saskatchewan Soil Conservation Association (SSCA) encourage farmers to adopt no-till practices in return for carbon offset credits. In the USA, the Pacific Northwest Direct Seed Association offers soil carbon credits generated from no-till management to an energy company The Chicago Climate Exchange (CCX) (www.chicagoclimatex.com/) allows GHG offsets from no-tillage and conversion of cropland to grasslands to be traded by voluntary action through a market trading mechanism. These approaches to agriculturally derived GHG offset will likely expand geographically and in scope. Policy instruments are detailed in Chapter 13 (Section 13.2).
Chapter 8
8.6.2
Agriculture
Barriers and opportunities/implementation issues
The commonly mentioned barriers to adoption of carbon sequestration activities on agricultural lands include the following: Maximum Storage: Carbon sequestration in soils or terrestrial biomass has a maximum capacity for the ecosystem, which may be reached after 15 to 60 years, depending on management practice, management history, and the system (West and Post, 2002). However, sequestration is a rapidly and cheaply deployable mitigation option, until more capital-intensive developments, and longer-lasting actions become available (Caldeira et al., 2004; Sands and McCarl, 2005). Reversibility: A subsequent change in management can reverse the gains in carbon sequestration over a similar period of time. Not all agricultural mitigation options are reversible; reduction in N2O and CH4 emissions, avoided emissions as a result of agricultural energy efficiency gains or substitution of fossil fuels by bio-energy are non-reversible. Baseline: The GHG net emission reductions need to be assessed relative to a baseline. Selection of an appropriate baseline to measure management-induced soil carbon changes is still an obstacle in some mitigation projects. The extent of practices already in place in project regions will need to be determined for the baseline. Uncertainty: This has two components: mechanism uncertainty and measurement uncertainty. Uncertainty about the complex biological and ecological processes involved in GHG emissions and carbon storage in agricultural systems makes investors more wary of these options than of more clearcut industrial mitigation activities. This barrier can be reduced by investment in research. Secondly, agricultural systems exhibit substantial variability between seasons and locations, creating high variability in offset quantities at the farm level. This variability can be reduced by increasing the geographical extent and duration of the accounting unit (e.g., multi-region, multi-year contracts; Kim and McCarl, 2005). Displacement of Emissions: Adopting certain agricultural mitigation practices may reduce production within implementing regions, which, in turn, may be offset by increased production outside the project region unconstrained by GHG mitigation objectives, reducing the net emission reductions. ‘Wall-to-wall’ accounting can detect this, and crediting correction factors may need to be employed (Murray et al., 2004; US-EPA, 2005).
smallholders. For example, a 50 kt contract needs 25 kha under soil carbon management (uptake ~ 2 tCO2 ha/yr). In developing countries, this could involve many thousands of farmers. Measurement and monitoring costs: Mooney et al. (2004) argue that such costs are likely to be small (under 2% of the contract), but other studies disagree (Smith, 2004c). In general, measurement costs per carbon-credit sold decrease as the quantity of carbon sequestered and area sampled increase. Methodological advances in measuring soil carbon may reduce costs and increase the sensitivity of change detection. However, improved methods to account for changes in soil bulk density remain a hindrance to quantification of changes in soil carbon stocks (Izaurralde and Rice, 2006). Development of remote sensing, new spectral techniques to measure soil carbon, and modelling offer opportunities to reduce costs but will require evaluation (Izaurralde and Rice, 2006, Brown et al., 2006; Ogle and Paustian, 2005; Gehl and Rice, 2007). Property rights: Property rights, landholdings, and the lack of a clear single-party land ownership in certain areas may inhibit implementation of management changes. Other barriers: Other possible barriers to implementation include the availability of capital, the rate of capital stock turnover, the rate of technological development, risk attitudes, need for research and outreach, consistency with traditional practices, pressure for competing uses of agricultural land and water, demand for agricultural products, high costs for certain enabling technologies (e.g., soil tests before fertilization), and ease of compliance (e.g., straw burning is quicker than residue removal and can also control some weeds and diseases, so farmers favour straw burning).
8.7 Integrated and non-climate policies affecting emissions of GHGs Many policies other than climate policies affect GHG emissions from agriculture. These include other UN conventions such as Biodiversity, Desertification and actions on Sustainable Development (see Section 8.4.5), macroeconomic policy such as EU Common Agricultural Policy (CAP)/CAP reform, international free trade agreements, trading blocks, trade barriers, region-specific programmes, energy policy and price adjustment, and other environmental policies including various environmental/agro-environmental schemes. These are described further below. 8.7.1
Transaction costs: Under an incentive-based system such as a carbon market, the amount of money farmers receive is not the market price, but the market price less brokerage cost. This may be substantial, and is an increasing fraction as the amount of carbon involved diminishes, creating a serious entry barrier for
Other UN conventions
In Asia, China has introduced laws to convert croplands to forest and grassland in Vulnerable Ecological Zones under the UN Convention on Desertification. This will increase carbon storage and reduce N2O emissions. Under the UN Convention 525
Agriculture
on Biodiversity, China has initiated a programme that restores croplands close to lakes, the sea, or other natural lands as conservation zones for wildlife. This may increase soil carbon sequestration but, if restored to wetland, could increase CH4 emissions. In support of UN Sustainable Development guidelines, China has introduced a Land Reclamation Regulation (1988) in which land degraded by, for example, construction or mining is restored for use in agriculture, thereby increasing soil carbon storage. In Europe (including Eastern Europe, the Caucasus and Central Asia) and North America, the UN conventions have had few significant impacts on agricultural GHG emissions. In Europe, the UN Convention on Long Range Trans-boundary Air Pollutants also leads to regulations to control air pollutants (e.g., by regulating N emissions) that could have substantial impacts on emission reductions in the agricultural sector. 8.7.2
Macroeconomic and sectoral policy
Some macro-economic changes, such as the burden of a high external debt in Latin America, triggered the adoption in the 1970s of policies designed for improving the trade balance, mainly by promoting agricultural exports (Tejo, 2004). This resulted in the changes in land use and management (see Section 8.3.3), which are still causing increases in annual GHG emissions today. In other regions, such as the countries of Eastern Europe, the Caucasus and Central Asia and many Central and East European countries, political changes since 1990 have meant agricultural de-intensification with less inputs, and land abandonment, leading to a decrease in agricultural GHG emissions. In Africa, the cultivated area in Southern Africa has increased by 30% since 1960, while agricultural production has doubled (Scholes and Biggs, 2004). The macroeconomic development framework for Africa (NEPAD, 2005) emphasises agriculture-led development. It is, therefore, anticipated that the cropped area will continue to increase, especially in Central, East, and Southern Africa, perhaps at an accelerating rate. In Western Europe, North America, Asia (China) and Oceania, macroeconomic policy has tended to reduce GHG emissions. The declining emission trend in Western Europe is likely a consequence of successive reforms of the Common Agricultural Policy (CAP) since 1992. The 2003 EU CAP reform is expected to lead to further reductions, mainly through reduction of animal numbers (Binfield et al., 2006). The reduced GHG emissions could be offset by activity elsewhere. Various macro-economic policies that potentially affect agricultural GHG emissions in each major world region are presented in Table 8.10. WTO negotiations, to the extent they move toward free trade, would permit countries to better adjust to climate change and the dislocations in production caused by mitigation activities, by adjusting their import/export mix. International trade agreements such as WTO may also have impacts on the amount and geographical distribution of GHG emissions. If agricultural subsidies are reduced and markets become more open, a shift in production from developed to developing countries would be expected, with the consequent displacement of GHG emissions 526
Chapter 8
to the latter. Since agricultural practices and GHG emissions per unit product differ between countries, such displacement may also cause changes in total emissions from agriculture. In addition, the increase in international flow of agricultural products which may result from trade liberalization could cause higher GHG emissions from the use of transport fuels. 8.7.3
Other environmental policies
In most world regions, environmental policies have been put in place to improve fertility, to reduce erosion and soil loss, and to improve agricultural efficiency. The majority of these environmental policies also reduce GHG emissions. Various environmental policies not implemented specifically to address GHG emissions but potentially affect agricultural GHG emissions in each major world region are presented in Table 8.11. In all regions, policies to improve other aspects of the environment have been more effective in reducing GHG emissions from agriculture than policies aimed specifically at reducing agricultural GHG emissions (see Section 8.6.1). The importance of identifying these co-benefits when formulating climate and other environmental policy is addressed in Section 8.8.
8.8 Co-benefits and trade-offs of mitigation options Many of the measures aimed at reducing GHG emissions have other impacts on the productivity and environmental integrity of agricultural ecosystems, mostly positive (Table 8.12). These measures are often adopted mainly for reasons other than GHG mitigation (see Section 8.7.3). Agro-ecosystems are inherently complex and very few practices yield purely winwin outcomes; most involve some trade-offs (DeFries et al., 2004; Viner et al., 2006) above certain levels or intensities of implementation. Specific examples of co-benefits and tradeoffs among agricultural GHG mitigation measures include: • Practices that maintain or increase crop productivity can improve global or regional food security (Lal, 2004a, b; Follett et al., 2005). This co-benefit may become more important as global food demands increase in coming decades (Sanchez and Swaminathan, 2005; Rosegrant and Cline, 2003; FAO, 2003; Millennium Ecosystem Assessment, 2005). Building reserves of soil carbon often also increases the potential productivity of these soils. Furthermore, many of the measures that promote carbon sequestration also prevent degradation by avoiding erosion and improving soil structure. Consequently, many carbon conserving practices sustain or enhance future fertility, productivity and resilience of soil resources (Lal, 2004a; Cerri et al., 2004; Freibauer et al., 2004; Paustian et al., 2004; Kurkalova
• •
Asia Oceania
Note: + denotes a positive effect (benefit); - denotes a negative effect
•
•
• •
• • •
Africa
Europe, the Caucasus and Central Asia
Latin America
• • • •
North America
Energy conservation and energy security policies – promote bio-energy – increase fossil fuel offsets and possibly SOC (USA) Energy price adjustments - encourage agricultural mitigation - more reduced tillage – increase SOC (USA) Removal of the Grain Transportation Subsidy shifted production from annual to perennial crops and livestock (Canada) Policies since 1970s to promote agricultural products exports (Tejo, 2004) resulting in land management change –increasing GHG emissions (Latin America) Promotion of biofuels (e.g., PROALCOOL (Brazil) Brazil and Argentina implemented policies to make compulsory 5% biodiesel in all diesel fuels consumed (Brazil & Argentina) Common Agricultural Policy (CAP) 2003 - Single Farm Payment decoupled from production - replaces most of the previous areabased payments. Income support conditional to statutory environmental management requirements (e.g., legislation on nitrates) and the obligation to maintain land under permanent pasture (cross-compliance). Political changes in Eastern Europe - closure of many intensive pig units - reduced GHG emissions (EU and wider Europe) Macro-economic changes in the countries of Eastern Europe, the Caucasus and Central Asia: a) Abandonment of croplands since 1990 (1.5 Mha); grasslands and regenerating forests sequestering carbon in soils and woody biomass (all countries of Eastern Europe, the Caucasus and Central Asia:) b) Use of agricultural machinery declined and fossil fuel use per ha of cropland (Romanenkov et al., 2004) - decreased CO2 (fossil fuel) increased CO2 (straw burning – all countries of Eastern Europe, the Caucasus and Central Asia) c) Fertilizer consumption has dropped; 1999 N2O emissions from agriculture 19.5% of 1990 level (Russia & Belarus). d) CO2 emissions from liming have dropped to 8% of 1990 levels (Russia) e) Livestock CH4 emissions in 1999 were less than 48% of the 1990 level (Russia) f) The use of bare fallowing has declined (88% of the area in bare fallow in 1999 compared to 1990; Agriculture of Russia, 2004) (Russia) g) Changes in rotational structure (more perennial grasses) (Russia) The cultivated area in Southern Africa has increased 30% since 1960, while agricultural production has doubled - agriculture-led development (Scholes and Biggs 2004; NEPAD 2005).Cropped area will continue to increase, especially in Central, East and Southern Africa, perhaps at an accelerating rate. In some areas, croplands are currently in set-aside for economic reasons (China) Australia and New Zealand continue to provide little direct subsidy to agriculture - highly efficient industries that minimize unnecessary inputs and reduce waste - potential for high losses (such as N2O) is reduced. Continuing tightening of terms of trade for farm enterprises, as well as ongoing relaxation of requirements for agricultural imports, is likely to maintain this focus (Australia and New Zealand) The establishment of comprehensive water markets are expected, over time, to result in reductions in the size of industries such as rice and irrigated dairy with consequent reductions in the emissions from these sectors (Australia)
Macro-economic policies potentially affecting agricultural GHG emissions
Region
+
-
+ +
+
+ +
-
+
+
+ +
+
+
+
+
+ + +
+
-
+
+
Impact Impact Impact on CO2 on N2O on CH4 emissions emissions emissions + + ? + + + -
Table 8.10: Summary of various macro-economic policies that potentially affect agricultural GHG emissions, listing policies for each major world region and the potential impact on the emissions of each GHG
Chapter 8 Agriculture
527
528
Note: + denotes a positive effect (benefit); - denotes a negative effect
•
•
•
• • • • • •
Asia
Oceania
•
• • • • •
• • • •
• • • •
•
• •
Africa
Europe, the Caucasus and Central Asia
Latin America
• • • • •
• • •
North America
Impact on Impact on Impact on CO2 N2 O CH4 emissions emissions emissions Environmental Quality Incentives Program (EQIP) – cost-sharing and incentive payments for conservation practices on working farms (USA) + + Conservation Reserve Program (CRP) - environmentally sensitive land converted to native grasses, trees, etc. (USA) + + Conservation Security Program (CSP) – assistance promoting conservation on cropland, pasture and range land (and farm woodland) + + (USA) + + Green cover in Canada and provincial initiatives – encourages shift from annual to perennial crop production on poor quality soils (Canada) + + + Agriculture Policy Framework (APF) programmes to reduce agriculture risks to the environment, including GHG emissions (Canada) + + + Nutrient Management programmes – introduced to improve water quality, may indirectly reduce N2O emissions (Canada) Increasing adoption of environmental policies driven by globalization, consolidation of democratic regimes (Latin America & Caribbean) +/+/+/14 countries have introduced environmental regulations over the last 20 years – most have implemented measures to protect the + ? environment + ? Promotion of no-till agriculture in the Mercosur area (Brazil, Argentina, Uruguay and Paraguay) + “Program Crop-Livestock Integration” promotes soil carbon, reduced erosion, reduced pathogens, fertility for pastures, no till cropping (Brazil) + EU set aside programme - encouraged carbon sequestering practices, but now replaced by the single farm payment under the new CAP + (EU) + EU/number of member states - soil action plans to promote soil quality/health/ sustainability, encourages soil carbon sequestration (EU) ? + Encouragement of composting in some EU member states (e.g., Belgium; Sleutel 2005), but policies are limited (Smith et al., 2005a) (EU) + + + EU Water Framework Directive (WFD) promotes careful use of N fertilizer. Impact of WFD on agricultural GHG emissions as yet unclear (EU) + The ban of burning of field residues in the 1980s (for air quality purposes) enhance soil carbon, reduce N2O and CH4 (Smith et al., 1997; 2000) (EU) + The dumping ban at sea of sewage sludge in Europe in 1998 - more sludge reached agricultural land (Smith et al., 2000; 2001) (EU) + "Vandmiljøplaner" (water environmental plans) for the agricultural sector with clear effect (decrease) of GHGs (Denmark) + Land Codes of the Russian Federation, Belarus and the Ukraine - land conservation for promoting soil quality restoration and protection + “Land Reform Development in Russian Federation” & “Fertility 2006-2010” - plans to promote soil conservation/fertility/sustainability + + (Russia) + + Ukrainian law “Land protection” - action plans to promote soil conservation/increase commercial yields/fertility/sustainability (Ukraine) + ? Laws in Belarus such as “State Control of Land Use and Land Protection” encourages carbon sequestration (Belarus) + + Laws in the Ukraine to promote conversion of degraded lands to set-aside (Ukraine) Water quality initiatives, for example, Water Codes encourage reforestation and grassland riparian zones (Russia, Ukraine and Belarus) The ban of fertilizer application in some areas - reduce N2O emissions (Russia, Belarus, Ukraine) & regional programmes for example, Revival of the Volga The reduction of the area of rangelands burned - objective of both colonial and post-colonial administrations; renewed efforts (South + + + Africa, 1998) + Soil sustainability programmes - N fertilizer added to soils only after soil N testing (China) + Regional agricultural development programmes - enhance soil carbon storage (China) + Water quality programmes that control non-point source pollution (China) + + + Air quality legislation - bans straw burning, thus reducing CO2 (and CH4 and N2O) emissions (China) “Township Enterprises” & “Ecological Municipality” - reduce waste disposal, chemical fertilizer and pesticides, and bans straw burning (China) + + + Wide range of policies to maintain function/conservation of agricultural landscapes, river systems and other ecosystems (Australia and + New Zealand) + + Industry changes leading to rapid increase in N fertilizer use over the past decade (250% and 500% increases in Australia and New + + Zealand, respectively) + + + Increases in intensive livestock production; raised concerns about water quality and the health of riverine/offshore ecosystems (Australia and New Zealand) Policy responses are being developed that include monitoring, regulatory, research and extension components (Australia and New Zealand)
Other environmental policies potentially affecting agricultural GHG emissions
Region
Table 8.11: A non-exhaustive summary of environmental policies that were not implemented specifically to address GHG emissions, but that can affect agricultural GHG emissions. Examples of policies are listed for major world region and the potential impact on the emissions of each GHG is indicated.
Agriculture Chapter 8
Examples Agronomy Nutrient management Tillage/residue management Water management (irrigation, drainage) Rice management Agro-forestry Set-aside, land-use change Grazing intensity Increased productivity (e.g., fertilization) Nutrient management Fire management Species introduction (including legumes) Avoid drainage of/restore wetlands Erosion control, organic amendments, nutrient amendments Improved feeding practices Specific agents and dietary additives Longer term structural and management changes and animal breeding Improved storage and handling Anaerobic digestion More efficient use as nutrient source Energy crops, solid, liquid, biogas, residues References (see footnotes) + a
b
+
+/-
+
+/+/+
+/+ +/+/+ +/+
Food security (productivity) + -/+ + + + +/+/+ + + + + + + + +
Water conservation c
+
+ +/+/+
+/-
Soil quality d
+
+
+ + + +/-
+
+ +
+ + + +/-
Air quality e
+/+ +
+
+
+/-
+/+
Bio-diversity, wildlife habitat f
+ +
+ +/-
+ + +
+
+/-
Energy conservation + + + g
+ +
-
+ +
+ + -
Conservation of other biomes h
+ +
+
-
+ +
+
i
+ +
+/+/-
+ +
+/-
Aesthetic/ amenity value
Note:+ denotes a positive effect (benefit); - denotes a negative effect (trade-off). The co-benefits and trade-offs vary among regions. Economic costs and benefits, often key driving variables, are considered in Section 8.4.3 Sources: a Foley et al., 2005; Lal, 2001a, 2004a; b Mosier, 2002; Freibauer et al., 2004; Paustian et al., 2004; Cerri et al.., 2004 c Lal, 2002, 2004b; Dias de Oliveira et al., 2005; Rockström, 2003. d Lal, 2001b, Janzen, 2005; Cassman et al., 2003; Cerri et al., 2004; Wander and Nissen, 2004 e Mosier, 2001; 2002; Paustian et al.., 2004 f Foley et al.., 2005; Dias de Oliveira et al., 2005; Freibauer et al., 2004; Falloon et al., 2004; Huston and Marland, 2003; Totten et al., 2003 g Lal et al., 2003; West and Marland, 2003 h Balmford et al., 2005; Trewavas, 2002; Green et al., 2005; West and Marland, 2003 i Freibauer et al., 2004
Bioenergy
Manure/biosolid management
Management of organic soils Restoration of degraded lands Livestock management
Grazing land management/ pasture improvement
Measure Cropland management
Water quality
Table 8.12: Summary of possible co-benefits and trade-offs of mitigation options in agriculture.
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•
•
•
•
•
et al., 2004; Díaz-Zorita et al., 2002). In some instances, where productivity is enhanced through increased inputs, there may be risks of soil depletion through mechanisms such as acidification or salinization (Barak et al., 1997; Díez et al., 2004; Connor, 2004). A key potential trade-off is between the production of bioenergy crops and food security. To the extent that bio-energy production uses crop residues, excess agricultural products or surplus land and water, there will be little resultant loss of food production. But above this point, proportional losses of food production will be strongly negative. Food insecurity is determined more by inequity of access to food (at all scales) than by absolute food production insufficiencies, so the impact of this trade-off depends among other things on the economic distributional effects of bio-energy production. Fresh water is a dwindling resource in many parts of the world (Rosegrant and Cline, 2003; Rockström, 2003). Agricultural practices for mitigation of GHGs can have both negative and positive effects on water conservation, and on water quality. Where measures promote water use efficiency (e.g., reduced tillage), they provide potential benefits. But in some cases, the practices could intensify water use, thereby reducing stream flow or groundwater reserves (Unkovich, 2003; Dias de Oliveira et al., 2005). For instance, high-productivity, evergreen, deep-rooted bio-energy plantations generally have a higher water use than the land cover they replace (Berndes, 2002, Jackson et al., 2005). Some practices may affect water quality through enhanced leaching of pesticides and nutrients (Freibauer et al., 2004; Machado and Silva, 2001). If bio-energy plantations are appropriately located, designed, and managed, they may reduce nutrient leaching and soil erosion and generate additional environmental services such as soil carbon accumulation, improved soil fertility; removal of cadmium and other heavy metals from soils or wastes. They may also increase nutrient recirculation, aid in the treatment of nutrient-rich wastewater and sludge; and provide habitats for biodiversity in the agricultural landscape (Berndes and Börjesson, 2002; Berndes et al. 2004; Börjesson and Berndes, 2006). Changes to land use and agricultural management can affect biodiversity, both positively and negatively (e.g., Xiang et al., 2006; Feng et al., 2006). For example, intensification of agriculture and large-scale production of biomass energy crops will lead to loss of biodiversity where they occur in biodiversity-rich landscapes (European Environment Agency, 2006). But perennial crops often used for energy production can favour biodiversity, if they displace annual crops or degraded areas (Berndes and Börjesson, 2002). Agricultural mitigation practices may influence non-agricultural ecosystems. For example, practices that diminish productivity in existing cropland (e.g., set-aside lands) or divert products to alternate uses (e.g., bio-energy crops) may induce conversion of forests to cropland elsewhere.
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Conversely, increasing productivity on existing croplands may ‘spare’ some forest or grasslands (West and Marland, 2003; Balmford et al., 2005; Mooney et al., 2005). The net effect of such trade-offs on biodiversity and other ecosystem services has not yet been fully quantified (Huston and Marland, 2003; Green et al., 2005). • Agro-ecosystems have become increasingly dependent on input of reactive nitrogen, much of it added as manufactured fertilizers (Galloway et al., 2003; Galloway, 2004). Practices that reduce N2O emission often improve the efficiency of N use from these and other sources (e.g., manures), thereby also reducing GHG emissions from fertilizer manufacture and avoiding deleterious effects on water and air quality from N pollutants (Oenema et al., 2005; Dalal et al., 2003; Olesen et al., 2006; Paustian et al., 2004). Suppressing losses of N as N2O might in some cases increase the risk of losing that N via leaching. Curtailing supplemental N use without a corresponding increase in N-use efficiency will restrict yields, thereby hampering food security. • Implementation of agricultural GHG mitigation measures may allow expanded use of fossil fuels, and may have some negative effects through emissions of sulphur, mercury and other pollutants (Elbakidze and McCarl, 2007). The co-benefits and trade-offs of a practice may vary from place to place because of differences in climate, soil, or the way the practice is adopted. In producing bio-energy, for example, if the feedstock is crop residue, that may reduce soil quality by depleting soil organic matter. Conversely, if the feedstock is a densely rooted perennial crop that may replenish organic matter and thereby improve soil quality (Paustian et al., 2004).These few examples, and the general trends described in Table 8.12, demonstrate that GHG mitigation practices on farm lands exert complex, interactive effects on the environment, sometimes far from the site at which they are imposed. The merits of a given practice, therefore, cannot be judged solely on effectiveness of GHG mitigation.
8.9 Technology research, development, deployment, diffusion and transfer
There is much scope for technological developments to reduce GHG emissions in the agricultural sector. For example, increases in crop yields and animal productivity will reduce emissions per unit of production. Such increases in crop and animal productivity will be implemented through improved management and husbandry techniques, such as better management, genetically modified crops, improved cultivars, fertilizer recommendation systems, precision agriculture, improved animal breeds, improved animal nutrition, dietary additives and growth promoters, improved animal fertility, bioenergy crops, anaerobic slurry digestion and methane capture
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systems. All of these depend to some extent on technological developments. Although technological improvement may have very significant effects, transfer of these technologies is a key requirement for these mitigations to be realized. For example, the efficiency of N use has improved over the last two decades in developed countries, but continues to decline in many developing countries due to barriers to technology transfer (International Fertilizer Industry Association, 2007). Based on technology change scenarios developed by Ewert et al. (2005), and derived from extrapolation of current trends in FAO data, Smith et al. (2005b) showed that technological improvements could potentially counteract the negative impacts of climate change on cropland and grassland soil carbon stocks in Europe. This and other work (Rounsevell et al., 2006) suggest that technological improvement will be a key factor in GHG mitigation in the future. In most instances, the cost of employing mitigation strategies will not alter radically in the medium term. There will be some shifts in costs due to changes in prices of agricultural products and inputs, but these are unlikely to be of significant magnitude. Likewise, the potential of most options for CO2 reduction is unlikely to change greatly. There are some exceptions which fall into two categories: (i) options where the practice or technology is not new, but where the emission reduction potential has not been adequately quantified, such as improved nutrient utilization; and (ii) options where technologies are still being refined such as probiotics in animal diets, or nitrification inhibitors. Many of the mitigation strategies outlined for agriculture employ existing technology (e.g., crop management, livestock management). With such strategies, the main issue is technology transfer, diffusion, and deployment. Other strategies involve new use of existing technologies. For example, oils have been used in animal diets for many years to increase dietary energy content, but their role as a methane suppressant is relatively new, and the parameters of the technology in terms of scope for methane reduction are only now being defined. Other strategies still require further research to allow viable systems to operate (e.g., bio-energy crops). Finally, many novel mitigation strategies are presently being refined, such as the use of probiotics, novel plant extracts, and the development of vaccines. Thus, there is still a major role for research and development in this area. Differences between regions can arise due to the state of development of the agricultural industry, the resources available and legislation. For example, the scope to use specific agents and dietary additives in ruminants is much greater in developed than in the developing regions because of cost, opportunity (e.g., it is easier to administer products to animals in confined systems than in free ranging or nomadic systems), and availability of the technology (US-EPA, 2006a). Furthermore, certain technologies are not allowed in some regions, for example, ionophores are banned from use in animal feeding in the EU, and genetically modified crops are not approved for use in some countries.
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8.10
Long-term outlook
Trends in GHG emissions in the agricultural sector depend mainly on the level and rate of socio-economic development, human population growth, and diet, application of adequate technologies, climate and non-climate policies, and future climate change. Consequently, mitigation potentials in the agricultural sector are uncertain, making a consensus difficult to achieve and hindering policy making. However, agriculture is a significant contributor to GHG emissions (Section 8.2). Mitigation is unlikely to occur without action, and higher emissions are projected in the future if current trends are left unconstrained. According to current projections, the global population will reach 9 billion by 2050, an increase of about 50% over current levels (Lutz et al., 2001; Cohen, 2003). Because of these increases and changing consumption patterns, some analyses estimate that the production of cereals will need to roughly double in coming decades (Tilman et al., 2001; Roy et al., 2002; Green et al., 2005). Achieving these increases in food production may require more use of N fertilizer, leading to possible increases in N2O emissions, unless more efficient fertilization techniques and products can be found (Galloway, 2003; Mosier, 2002). Greater demands for food could also increase CH4 emissions from enteric fermentation if livestock numbers increase in response to demands for meat and other livestock products. As projected by the IMAGE 2.2 model, CO2, CH4, and N2O emissions associated with land use vary greatly between scenarios (Strengers et al., 2004), depending on trends towards globalization or regionalization, and on the emphasis placed on material wealth relative to sustainability and equity. Some countries are moving forward with climate and nonclimate policies, particularly those linked with sustainable development and improving environmental quality as described in Sections 8.6 and 8.7. These policies will likely have direct or synergistic effects on GHG emissions and provide a way forward for mitigation in the agricultural sector. Moreover, global sharing of innovative technologies for efficient use of land resources and agricultural inputs, in an effort to eliminate poverty and malnutrition, will also enhance the likelihood of significant mitigation from the agricultural sector. Mitigation of GHG emissions associated with various agricultural activities and soil carbon sequestration could be achieved through best management practices, many of which are currently available for implementation. Best management practices are not only essential for mitigating GHG emissions, but also for other facets of environmental protection such as air and water quality management. Uncertainties do exist, but they can be reduced through finer scale assessments of best management practices within countries, evaluating not only the GHG mitigation potential but also the influences of mitigation options on socio-economic conditions and other environmental impacts. 531
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The long-term outlook for development of mitigation practices for livestock systems is encouraging. Continuous improvements in animal breeds are likely, and these will improve the GHG emissions per kg of animal product. Enhanced production efficiency due to structural change or better application of existing technologies is also generally associated with reduced emissions, and there is a trend towards increased efficiency in both developed and developing countries. New technologies may emerge to reduce emissions from livestock such as probiotics, a methane vaccine or methane inhibitors. However, increased world demand for animal products may mean that while emissions per kg of product decline, total emissions may increase. Recycling of agricultural by-products, such as crop residues and animal manures, and production of energy crops provides opportunities for direct mitigation of GHG emissions from fossil fuel offsets. However, there are barriers in technologies and economics to using agricultural wastes, and in converting energy crops into commercial fuels. The development of innovative technologies is a critical factor in realizing the potential for biofuel production from agricultural wastes and energy crops. This mitigation option could be moved forward with government investment for the development of these technologies, and subsidies for using these forms of energy. A number of agricultural mitigation options which have limited potential now will likely have increased potential in the long-term. Examples include better use of fertilizer through precision farming, wider use of slow and controlled release fertilizers and of nitrification inhibitors, and other practices that reduce N application (and thus N2O emissions). Similarly, enhanced N-use efficiency is achievable as technologies such as field diagnostics, fertilizer recommendations from expert/ decision support systems and fertilizer placement technologies are developed and more widely used. New fertilizers and water management systems in paddy rice are also likely in the longer term. Possible changes to climate and atmosphere in coming decades may influence GHG emissions from agriculture, and the effectiveness of practices adopted to minimize them. For example, atmospheric CO2 concentrations, likely to double within the next century, may affect agro-ecosystems through changes in plant growth rates, plant litter composition, drought tolerance, and nitrogen demands (e.g., Long et al., 2006; Henry et al., 2005; Van Groenigen et al., 2005; Jensen and Christensen, 2004; Torbert et al., 2000; Norby et al., 2001). Similarly, atmospheric nitrogen deposition also affects crop production systems as well as changing temperature regimes, although the effect will depend on the magnitude of change and response of the crop, forage, or livestock species. For example, increasing temperatures are likely to have a positive effect on crop production in colder regions due to a longer growing season (Smith et al., 2005b). In contrast, increasing temperatures could accelerate decomposition of soil organic matter, releasing 532
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stored soil carbon into the atmosphere (Knorr et al., 2005; Fang et al., 2005; Smith et al. 2005b). Furthermore, changes in precipitation patterns could change the adaptability of crops or cropping systems selected to reduce GHG emissions. Many of these effects have high levels of uncertainty; but demonstrate that practices chosen to reduce GHG emissions may not have the same effectiveness in coming decades. Consequently, programmes to reduce emissions in the agricultural sector will need to be designed with flexibility for adaptation in response to climate change. Overall, the outlook for GHG mitigation in agriculture suggests significant potential. Current initiatives suggest that identifying synergies between climate change policies, sustainable development, and improvement of environmental quality will likely lead the way forward to realization of mitigation potential in this sector.
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9 Forestry Coordinating Lead Authors: Gert Jan Nabuurs (The Netherlands), Omar Masera (Mexico)
Lead Authors: Kenneth Andrasko (USA), Pablo Benitez-Ponce (Equador), Rizaldi Boer (Indonesia), Michael Dutschke (Germany), Elnour Elsiddig (Sudan), Justin Ford-Robertson (New Zealand), Peter Frumhoff (USA), Timo Karjalainen (Finland), Olga Krankina (Russia), Werner A. Kurz (Canada), Mitsuo Matsumoto (Japan), Walter Oyhantcabal (Uruguay), Ravindranath N.H. (India), Maria José Sanz Sanchez (Spain), Xiaquan Zhang (China)
Contributing Authors: Frederic Achard (Italy), Carlos Anaya (Mexico), Sander Brinkman (The Netherlands), Wenjun Chen (Canada), Raymond E. (Ted) Gullison (Canada), Niro Higuchi (Brazil), Monique Hoogwijk (The Netherlands), Esteban Jobbagy (Argentina), G. Cornelis van Kooten (Canada), Franck Lecocq (France), Steven Rose (USA), Bernhard Schlamadinger (Austria), Britaldo Silveira Soares Filho (Brazil), Brent Sohngen (USA), Bart Strengers (The Netherlands), Eveline Trines (The Netherlands)
Review Editors: Mike Apps (Canada), Eduardo Calvo (Peru)
This chapter should be cited as: Nabuurs, G.J., O. Masera, K. Andrasko, P. Benitez-Ponce, R. Boer, M. Dutschke, E. Elsiddig, J. Ford-Robertson, P. Frumhoff, T. Karjalainen, O. Krankina, W.A. Kurz, M. Matsumoto, W. Oyhantcabal, N.H. Ravindranath, M.J. Sanz Sanchez, X. Zhang, 2007: Forestry. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Forestry
Chapter 9
Table of Contents Executive Summary .................................................. 543 9.1
Introduction ...................................................... 544
9.2
Status of the sector and trends ..................... 544
9.3
9.2.1
Forest area ...................................................... 544
9.2.2
Forest management ........................................ 546
9.2.3
Wood supply, production and consumption of forest products ................................................ 546
9.6
Regional and global trends in terrestrial greenhouse gas emissions and removals .... 546
9.4 Assessment of mitigation options ................. 547
9.5
9.4.1
Conceptual introduction ................................. 547
9.4.2
Description of mitigation measures ................. 549
9.4.3
Global assessments ........................................ 551
9.4.4
Global summation and comparison ................. 561
Interactions with adaptation and vulnerability .................................................... 563 9.5.1
Climate impacts on carbon sink and adaptation....................................................... 564
9.5.2
Mitigation and adaptation synergies................. 564
9.7
Effectiveness of and experience with policies ............................................................... 566 9.6.1
Policies aimed at reducing deforestation .......... 566
9.6.2
Policies aimed to promote afforestation and reforestation .................................................... 568
9.6.3
Policies to improve forest management ........... 568
9.6.4
Policies to increase substitution of forestderived biofuels for fossil fuels and biomass for energy-intensive materials ............................... 569
9.6.5
Strengthening the role of forest policies in mitigating climate change ................................ 569
9.6.6
Lessons learned from project-based afforestation and reforestation since 2000 ........ 571
Forests and Sustainable Development ....... 573 9.7.1
Conceptual aspects ........................................ 573
9.7.2
Ancillary effects of GHG mitigation policies ...... 574
9.7.3
Implications of mitigation options on water, biodiversity and soil......................................... 574
9.8
Technology, R&D, deployment, diffusion and transfer ...................................................... 576
9.9
Long-term outlook ........................................ 577
References ................................................................... 578
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EXECUTIVE SUMMARY During the last decade of the 20th century, deforestation in the tropics and forest regrowth in the temperate zone and parts of the boreal zone remained the major factors responsible for emissions and removals, respectively. However, the extent to which the carbon loss due to tropical deforestation is offset by expanding forest areas and accumulating woody biomass in the boreal and temperate zones is an area of disagreement between land observations and estimates by top-down models. Emissions from deforestation in the 1990s are estimated at 5.8 GtCO2/yr (medium agreement, medium evidence). Bottom-up regional studies show that forestry mitigation options have the economic potential at costs up to 100 US$/ tCO2-eq to contribute 1.3-4.2 GtCO2-eq/yr (average 2.7 GtCO2eq/yr) in 2030. About 50% can be achieved at a cost under 20 US$/tCO2-eq (around 1.6 GtCO2/yr) with large differences between regions. Global top-down models predict far higher mitigation potentials of 13.8 GtCO2-eq/yr in 2030 at carbon prices less than or equal to 100 US$/tCO2-eq. Regional studies tend to use more detailed data and a wider range of mitigation options are reviewed, Thus, these studies may more accurately reflect regional circumstances and constraints than simpler, more aggregate global models. However, regional studies vary in model structure, coverage, analytical approach, and assumptions (including baseline assumptions). In the sectoral comparison in Section 11.3, the more conservative estimate from regional studies is used. Further research is required to narrow the gap in the potential estimates from global and regional assessments (medium agreement, medium evidence). The carbon mitigation potentials from reducing deforestation, forest management, afforestation, and agro-forestry differ greatly by activity, regions, system boundaries and the time horizon over which the options are compared. In the short term, the carbon mitigation benefits of reducing deforestation are greater than the benefits of afforestation. That is because deforestation is the single most important source, with a net loss of forest area between 2000 and 2005 of 7.3 million ha/yr. Mitigation options by the forestry sector include extending carbon retention in harvested wood products, product substitution, and producing biomass for bioenergy. This carbon is removed from the atmosphere and is available to meet society’s needs for timber, fibre, and energy. Biomass from forestry can contribute 12-74 EJ/yr to energy consumption, with a mitigation potential roughly equal to 0.4-4.4 GtCO2/yr depending on the assumption whether biomass replaces coal or gas in power plants (medium agreement, medium evidence). In the long term, a sustainable forest management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual sustained yield of timber, fibre or energy from the forest, will generate the largest sustained mitigation benefit. Most mitigation activities require up-front investment with benefits and co-benefits typically accruing for many years
to decades. The combined effects of reduced deforestation and degradation, afforestation, forest management, agro-forestry and bioenergy have the potential to increase from the present to 2030 and beyond (medium agreement, medium evidence). Global change will impact carbon mitigation in the forest sector but the magnitude and direction of this impact cannot be predicted with confidence as yet. Global change may affect growth and decomposition rates, the area, type, and intensity of natural disturbances, land-use patterns, and other ecological processes (medium agreement, medium evidence). Forestry can make a very significant contribution to a low-cost global mitigation portfolio that provides synergies with adaptation and sustainable development. However, this opportunity is being lost in the current institutional context and lack of political will to implement and has resulted in only a small portion of this potential being realized at present (high agreement, much evidence). Globally, hundreds of millions of households depend on goods and services provided by forests. This underlines the importance of assessing forest sector activities aimed at mitigating climate change in the broader context of sustainable development and community impact. Forestry mitigation activities can be designed to be compatible with adapting to climate change, maintaining biodiversity, and promoting sustainable development. Comparing environmental and social co-benefits and costs with the carbon benefit will highlight tradeoffs and synergies, and help promote sustainable development (low agreement, medium evidence). Realization of the mitigation potential requires institutional capacity, investment capital, technology RD and transfer, as well as appropriate policies and incentives, and international cooperation. In many regions, their absence has been a barrier to implementation of forestry mitigation activities. Notable exceptions exist, however, such as regional successes in reducing deforestation rates and implementing large-scale afforestation programmes. Considerable progress has been made in technology development for implementation, monitoring and reporting of carbon benefits but barriers to technology transfer remain (high agreement, much evidence). Forestry mitigation activities implemented under the Kyoto Protocol, including the Clean Development Mechanism (CDM), have to date been limited. Opportunities to increase activities include simplifying procedures, developing certainty over future commitments, reducing transaction costs, and building confidence and capacity among potential buyers, investors and project participants (high agreement, medium evidence). While the assessment in this chapter identifies remaining uncertainties about the magnitude of mitigation benefits and costs, the technologies and knowledge required to implement mitigation activities exist today. 543
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9.1
Introduction
In the context of global change and sustainable development, forest management activities play a key role through mitigation of climate change. However, forests are also affected by climate change and their contribution to mitigation strategies may be influenced by stresses possibly resulting from it. Socioeconomically, global forests are important because many citizens depend on the goods, services, and financial values provided by forests. Within this context, mitigation options have to be sought. The world’s forests have a substantial role in the global carbon cycle. IPCC (2007a) reports the latest estimates for the terrestrial sink for the decade 1993-2003 at 3,300 MtCO2/yr, ignoring emissions from land-use change (Denman et al., 2007, Table 7.1). The most likely estimate of these emissions for 1990s is 5,800 MtCO2/yr, which is partly being sequestered on land as well (IPCC, 2007a). The IPCC Third Assessment Report (TAR) (Kauppi et al., 2001) concluded that the forest sector has a biophysical mitigation potential of 5,380 MtCO2/yr on average up until 2050, whereas the SR LULUCF (IPCC, 2000a) presented a biophysical mitigation potential on all lands of 11670 MtCO2/ yr in 2010 (copied in IPCC, 2001, p. 110). Forest mitigation options include reducing emissions from deforestation and forest degradation, enhancing the sequestration rate in existing and new forests, providing wood fuels as a substitute for fossil fuels, and providing wood products for more energy-intensive materials. Properly designed and implemented, forestry mitigation options will have substantial co-benefits in terms of employment and income generation opportunities, biodiversity and watershed conservation, provision of timber and fibre, as well as aesthetic and recreational services. Many barriers have been identified that preclude the full use of this mitigation potential. This chapter examines the reasons for the discrepancy between a large theoretical potential and substantial co-benefits versus the rather low implementation rate. Developments since TAR Since the IPCC Third Assessment Report (TAR), new mitigation estimates have become available from local to global scale (Sathaye et al., 2007) as well as major economic reviews and global assessments (Stern, 2006). There is early research into the integration of mitigation and adaptation options and the linkages to sustainable development (MEA, 2005a). There is increased attention to reducing emissions from deforestation as a low cost mitigation option, and with significant positive side-effects (Stern, 2006). There is some evidence that climate change impacts can also constrain the forest potential. There are 544
very few multiple land-use studies that examine a wider set of forest functions and economic constraints (Brown et al., 2004). Furthermore, the literature shows a large variation of mitigation estimates, partly due to the natural variability in the system, but partly also due to differences in baseline assumptions and data quality. In addition, Parties to the Convention are improving their estimates through the design of National Systems for Greenhouse Gas (GHG) Inventories. Basic problems remain. Few major forest-based mitigation analyses have been conducted using new primary data. There is still limited insight regarding impacts on soils, lack of integrated views on the many site-specific studies, hardly any integration with climate impact studies, and limited views in relation to social issues and sustainable development. Little new effort was reported on the development of global baseline scenarios of land-use change and their associated carbon balance, against which mitigation options could be examined. There is limited quantitative information on the cost-benefit ratios of mitigation interventions. Finally, there are still knowledge gaps in how forest mitigation activities may alter, for example, surface hydrology and albedo (IPCC, 2007b: Chapter 4). This chapter: a) provides an updated estimate of the economic mitigation potential through forests; b) examines the reasons for difference between a large theoretical potential and a low rate of implementation; and c) and integrates the estimates of the economic potential with considerations to both adaptation and mitigation in the context of sustainable development.
9.2 9.2.1
Status of the sector and trends
Forest area
The global forest cover is 3952 million ha (Table 9.1), which is about 30 percent of the world’s land area (FAO, 2006a). Most relevant for the carbon cycle is that between 2000 and 2005, gross deforestation continued at a rate of 12.9 million ha/yr. This is mainly as a result of converting forests to agricultural land, but also due to expansion of settlements, infrastructure, and unsustainable logging practices (FAO, 2006a; MEA, 2005b). In the 1990s, gross deforestation was slightly higher, at 13.1 million ha/yr. Due to afforestation, landscape restoration and natural expansion of forests, the most recent estimate of net loss of forest is 7.3 million ha/yr. The loss is still largest in South America, Africa and Southeast Asia (Figure 9.1). This net loss was less than that of 8.9 million ha/yr in the 1990s. Thus, carbon stocks in forest biomass decreased in Africa, Asia, and South America, but increased in all other regions. According to FAO (2006a), globally net carbon stocks in forest biomass decreased by about 4,000 MtCO2 annually between 1990 and 2005 (Table 9.1).
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Table 9.1: Estimates of forest area, net changes in forest area (negative numbers indicating decrease), carbon stock in living biomass, and growing stock in 1990, 2000, and 2005 Region Africa Asia
Forest area, (mill. ha)
Annual change (mill. ha/yr)
Carbon stock in living biomass (MtCO2)
Growing stock in 2005
2005
1990-2000
2000-2005
1990
2000
2005
million m3
63,5412
-4.4
-4.0
241,267
228,067
222,933
64,957
571,577
-0.8
1.0
150,700
130,533
119,533
47,111
1001,394
0.9
0.7
154,000
158,033
160,967
107,264
North and Central America
705,849
-0.3
-0.3
150,333
153,633
155,467
78,582
Oceania
206,254
-0.4
-0.4
42,533
41,800
41,800
7,361
Europea)
South America World
831,540
-3.8
-4.3
358,233
345,400
335,500
128,944
3,952,026
-8.9
-7.3
1,097,067
1,057,467
1,036,200
434,219
a) Including all of the Russian Federation Source: FAO, 2006a
The area of forest plantation was about 140 million ha in 2005 and increased by 2.8 million ha/yr between 2000 and 2005, mostly in Asia (FAO, 2006a). According to the Millennium Ecosystem Assessment (2005b) scenarios, forest area in industrialized regions will increase between 2000 and 2050 by about 60 to 230 million ha. At the same time, the forest area in the developing regions will decrease by about 200 to 490 million ha. In addition to the decreasing forest area globally, forests are severely affected by disturbances such as forest
fires, pests (insects and diseases) and climatic events including drought, wind, snow, ice, and floods. All of these factors have also carbon balance implications, as discussed in Sections 9.3 and 9.4. Such disturbances affect roughly 100 million ha of forests annually (FAO, 2006a). Degradation, defined as decrease of density or increase of disturbance in forest classes, affected tropical regions at a rate of 2.4 million ha/yr in the 1990s.
Figure 9.1: Net change in forest area between 2000 and 2005 Source: FAO, 2006a.
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Chapter 9
Forest management
Data on progress towards sustainable forest management were collected for the recent global forest resources assessment (FAO, 2006a). These data indicate globally there are many good signs and positive trends (intensive forest plantation and rising conservation efforts), but also negative trends continue (primary forests continue to become degraded or converted to agriculture in some regions). Several tools have been developed in the context of sustainable forest management, including criteria and indicators, national forest programmes, model forests and certification schemes. These tools can also support and provide sound grounds for mitigation of climate change and thus carbon sequestration. Nearly 90% of forests in industrialized countries are managed “according to a formal or informal management plan” (FAO, 2001). National statistics on forest management plans are not available for many developing countries. However, preliminary estimates show that at least 123 million ha, or about 6% of the total forest area in these countries is covered by a “formal, nationally approved forest management plan covering a period of at least five years.” Proper management plans are seen as prerequisites for the development of management strategies that can also include carbon-related objectives.
society’s needs for timber through intensive management of a smaller forest area creates opportunities for enhanced forest protection and conservation in other areas, thus contributing to climate change mitigation. With rather stable harvested volumes, the manufacture of forest products has increased as a result of improved processing efficiency. Consumption of forest products is increasing globally, particularly in Asia.
9.3 Regional and global trends in terrestrial greenhouse gas emissions and removals Mitigation measures will occur against the background of ongoing change in greenhouse gas emissions and removals. Understanding current trends is critical for evaluation of additional effects from mitigation measures. Moreover, the potential for mitigation depends on the legacy of past and present patterns of change in land-use and associated emissions and removals. The contribution of the forest sector to greenhouse gas emissions and removals from the atmosphere remained the subject of active research, which produced an extensive body of literature (Table 9.2 and IPCC, 2007a: Chapter 7 and 10).
Wood supply, production and consumption of forest products
Globally during the 1990s, deforestation in the tropics and forest regrowth in the temperate zone and parts of the boreal zone were the major factors responsible for emissions and removals, respectively (Table 9.2; Figure 9.2). However, the extent to which carbon loss due to tropical deforestation is offset by expanding forest areas and accumulating woody biomass in the boreal and temperate zones is the area of disagreement between land observations and estimates by top-down models. The top-down methods based on inversion of atmospheric transport models estimate the net terrestrial carbon sink for the 1990s, which is the balance of sinks in northern latitudes and source in tropics (Gurney et al., 2002). The latest estimates are consistent with the increase found in the terrestrial carbon sink in the 1990s over the 1980s.
Global wood harvest is about 3 billion m3 and has been rather stable in the last 15 years (FAO, 2006a). Undoubtedly, the amount of wood removed is higher, as illegally wood removal is not recorded. About 60% of removals are industrial roundwood; the rest is wood fuel (including fuelwood and charcoal). The most wood removal in Africa and substantial proportions in Asia and South America are non-commercial wood fuels. Recently, commercial biomass for bioenergy received a boost because of the high oil prices and the government policies initiated to promote renewable energy sources.
Denman et al. (2007) reports the latest estimates for gross residual terrestrial sink for the 1990s at 9,500 MtCO2/yr, while their estimate for emissions from deforestation amounts to 5,800 MtCO2/yr. The residual sink estimate is significantly higher than any land-based global sink estimate and in the upper range of estimates produced by inversion of atmospheric transport models (Table 9.2). It includes the sum of biases in estimates of other global fluxes (fossil fuel burning, cement production, ocean uptake, and land-use change) and the flux in terrestrial ecosystems that are not undergoing change in land use.
Although accounting for only 5% of global forest cover, forest plantations were estimated in 2000 to supply about 35% of global roundwood harvest and this percentage is expected to increase (FAO, 2006a). Thus, there is a trend towards concentrating the harvest on a smaller forest area. Meeting
Improved spatial resolution allowed separate estimates of the land-atmosphere carbon flux for some continents (Table 9.2). These estimates generally suggest greater sink or smaller source than the bottom-up estimates based on analysis of forest inventories and remote sensing of change in land-cover
Market-based development of environmental services from forests, such as biodiversity conservation, carbon sequestration, watershed protection, and nature-based tourism, is receiving attention as a tool for promoting sustainable forest management. Expansion of these markets may remain slow and depends on government intervention (Katila and Puustjärvi, 2004). Nevertheless, development of these markets and behaviour of forest owners may influence roundwood markets and availability of wood for conventional uses, thus potentially limiting substitution possibilities. 9.2.3
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(Houghton, 2005). While the estimates of forest expansion and regrowth in the temperate and boreal zones appear relatively well constrained by available data and consistent across published results, the rates of tropical deforestation are uncertain and hotly debated (Table 9.2; Fearnside and Laurance, 2004). Studies based on remote sensing of forest cover report lower rates than UN-ECE/FAO (2000) and lower carbon emissions carbon (Achard et al., 2004).
the effects of wild fires and other natural disturbances. There are indications that higher temperatures in boreal regions will increase fire frequency; possible drying of the Amazon basin would increase fire frequency there as well (Cox et al., 2004). Global emissions from fires in the 1997/98 El Nino year are estimated at 7,700 MtCO2/yr, 90% from tropics (Werf et al., 2004). The picture emerging from Table 9.2 is complex because available estimates differ in the land-use types included and in the use of gross fluxes versus net carbon balance, among other variables. This makes it impossible to set a widely accepted baseline for the forestry sector globally. Thus, we had to rely on the baselines used in each regional study separately (Section 9.4.3.1), or used in each global study (Section 9.4.3.3). However, this approach creates large uncertainty in assessing the overall mitigation potential in the forest sector. Baseline CO2 emissions from land-use change and forestry in 2030 are the same as or slightly lower than in 2000 (see Chapter 3, Figure 3.10).
Recent analyses highlight the important role of other carbon flows. These flows were largely overlooked by earlier research and include carbon export through river systems (Raymond and Cole, 2003), volcanic activity and other geological processes (Richey et al., 2002), transfers of material in and out of products pool (Pacala et al., 2001), and uptake in freshwater ecosystems (Janssens et al., 2003). Attribution of estimated carbon sink in forests to the shortand long-term effects of the historic land-use change and shifting natural disturbance patterns on one hand, and to the effects of N and CO2 fertilization and climate change on the other, remains problematic (Houghton, 2003b). For the USA, for example, the fraction of carbon sink attributable to changes in land-use and land management might be as high as 98% (Caspersen et al., 2000), or as low as 40% (Schimel et al., 2001). Forest expansion and regrowth and associated carbon sinks were reported in many regions (Table 9.2; Figure 9.2). The expanding tree cover in South Western USA is attributed to the long-term effects of fire control but the gain in carbon storage was smaller than previously thought. The lack of consensus on factors that control the carbon balance is an obstacle to development of effective mitigations strategies.
9.4
Assessment of mitigation options
In this section, a conceptual framework for the assessment of mitigation options is introduced and specific options are briefly described. Literature results are summarized and compared for regional bottom-up approaches, global forest sector models, and global top-down integrated model approaches. The assessment is limited to CO2 balances and economic costs of the various mitigation options. Broader issues including biodiversity, sustainable development, and interactions with adaptation strategies are discussed in subsequent sections. 9.4.1
Large year-to-year and decade scale variation of regional carbon sinks (Rodenbeck et al., 2003) make it difficult to define distinct trends. The variation reflects the effects of climatic variability, both as a direct impact on vegetation and through
Conceptual introduction
Terrestrial carbon dynamics are characterized by long periods of small rates of carbon uptake, interrupted by short periods of
EECCA
Europe
2000
1995
1900
1900
1995
USA
1855
1995
1900
1855
1995
1900
0 -1000
4000
Non-Annex I South Asia
Tropical America
2000
2000
1995
1900
1995
1900
1900
0
1995
0
1855
OECD Pacific 2000 1855
1995
1900
2000
1855
4000
4000
Non-Annex I East Asia 1855
0
0 1855
1855
1995 1900
Tropical Africa 2000 0
2000
1995
1900
0
0
North Africa & Middle East 1855
2000
0
1855
0
Canada
2000
2000
Figure 9.2: Historical forest carbon balance (MtCO2) per region, 1855-2000. Notes: green = sink. EECCA=Countries of Eastern Europe, the Caucasus and Central Asia. Data averaged per 5-year period, year marks starting year of period. Source: Houghton, 2003b.
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Table 9.2: Selected estimates of carbon exchange of forests and other terrestrial vegetation with the atmosphere (in MtCO2/yr) Regions
Annual carbon flux based on international statistics UN-ECE, 2000
Annual carbon flux during 1990s Based on inversion of atmospheric transport models
Based on land observations
MtCO2/yr OECD North America Separately: Canada USA OECD Pacific
340 610
1,833 ± 2,2009
0 ÷ 1,1005
2,090 ± 3,3372
293 ± 7331 0±7331
224
Europe
316
Countries in Transition Separately: Russia
495 ±
7526
0 ± 7331 51311
1,726
3,777 ± 3,4472
1,100 ± 2,9339 1,181 ÷ -1,5887
1,572
4,767 ± 2,9339
1,907± 4698
623 ± 3,5932
Northern Africa
-576 ±2353 -440 ± 1104 -1,283 ± 7331
Sub-Saharan Africa
Caribbean, Central and South America
-2,310
± 73312
Separately: Brazil Developing countries of South and East Asia and Middle East Separately: China
Global total
Annex I (excluding Russia)
-1,617 ± 9723 -1,577 ± 7334 -2,750 ± 1,1001
-2,493 ± 2,7132
-3,997 ± 1,8331 -1,734 ± 5503 -1,283 ± 5504
2,273 ± 2,4202
- 110 ± 7331 128 ± 9513 24914
4,767 ± 5,5009 2,567 ± 2,93310 4,9132 951617
-7,993 ± 2,9331 -3,300 ÷ 7,7005 -4,00015 -5,800 16 -848518 130019
Notes: Positive values represent carbon sink, negative values represent source. Sign ÷ indicates a range of values; sign ± indicates error term. Because of differences in methods and scope of studies (see footnotes), values from different publications are not directly comparable. They represent a sample of reported results. 1 Houghton 2003a (flux from changes in land use and land management based on land inventories); 2 Gurney et al., 2002 (inversion of atmospheric transport models, estimate for Countries in Transition applies to Europe and boreal Asia; estimate for China applies to temperate Asia); 3 Achard et al., 2004 (estimates based on remote sensing for tropical regions only); 4 DeFries, 2002 (estimates based on remote sensing for tropical regions only); 5 Potter et al., 2003 (NEP estimates based on remote sensing for 1982-1998 and ecosystem modelling, the range reflects inter-annual variability); 6 Janssens et al., 2003 (combined use of inversion and land observations; includes forest, agricultural lands and peatlands between Atlantic Ocean and Ural Mountains, excludes Turkey and Mediterranean isles); 7 Shvidenko and Nilson, 2003 (forests only, range represents difference in calculation methods); 8 Nilsson et al., 2003 (includes all vegetation); 9 Ciais et al., 2000 (inversion of atmospheric transport models, estimate for Russia applies to Siberia only); 10 Plattner et al., 2002 (revised estimate for 1980’s is 400±700); 11Nabuurs et al., 2003 (forests only); 12 Houghton et al., 2000 (Brazilian Amazon only, losses from deforestation are offset by regrowth and carbon sink in undisturbed forests); 13 Fang et al., 2005; 14 Pan et al., 2004, 15 FAO, 2006a (global net biomass loss resulting from deforestation and regrowth); 16 Denman et al.,2007 (estimate of biomass loss from deforestation), 17 Denman et al.,2007 (Residual terrestrial carbon sink), 18 EDGAR database for agriculture and forestry (see Chapter 1, Figure 1.3a/b (Olivier et al., 2005)). These include emissions from bog fires and delayed emissions from soils after land- use change, 19 (Olivier et al., 2005).
rapid and large carbon releases during disturbances or harvest. Depending on the stage of stand1 development, individual stands are either carbon sources or carbon sinks (1m3 of wood
1 2
stores ~ 0.92 tCO2)2. For most immature and mature stages of stand development, stands are carbon sinks. At very old ages, ecosystem carbon will either decrease or continue to increase
In this chapter, ‘stand’ refers to an area of trees of similar characteristics (e.g., species, age, stand structure or management regime) while ‘forest’ refers to a larger estate comprising many stands. Assuming a specific wood density of 0.5g dry matter/cm3 and a carbon content of 0.5g C/g dry matter.
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slowly with accumulations mostly in dead organic matter and soil carbon pools. In the years following major disturbances, the losses from decay of residual dead organic matter exceed the carbon uptake by regrowth. While individual stands in a forest may be either sources or sinks, the forest carbon balance is determined by the sum of the net balance of all stands. The theoretical maximum carbon storage (saturation) in a forested landscape is attained when all stands are in old-growth state, but this rarely occurs as natural or human disturbances maintain stands of various ages within the forest. The design of a forest sector mitigation portfolio should consider the trade-offs between increasing forest ecosystem carbon stocks and increasing the sustainable rate of harvest and transfer of carbon to meet human needs (Figure 9.3). The selection of forest sector mitigation strategies should minimize net GHG emissions throughout the forest sector and other sectors affected by these mitigation activities. For example, stopping all forest harvest would increase forest carbon stocks, but would reduce the amount of timber and fibre available to meet societal needs. Other energy-intensive materials, such as concrete, aluminium, steel, and plastics, would be required to replace wood products, resulting in higher GHG emissions (Gustavsson et al., 2006). Afforestation may affect the net GHG balance in other sectors, if for example, forest expansion reduces agricultural land area and leads to farming practices with higher emissions (e.g., more fertilizer use), conversion of land for cropland expansion elsewhere, or increased imports of agricultural products (McCarl and Schneider, 2001). The choice of system boundaries and time horizons affects the ranking of mitigation activities (Figure 9.3). Forest mitigation strategies should be assessed within the framework of sustainable forest management, and with consideration of the climate impacts of changes to other processes such as albedo and the hydrological cycle (Marland et al., 2003). At present, however, few studies provide such comprehensive assessment.
Minimise net emissions to the atmosphere
Maximise carbon stocks
Non-forest land use
Biofuel
Fossil fuel
Wood products
Other products
Forest ecosystems
For the purpose of this discussion, the options available to reduce emissions by sources and/or to increase removals by sinks in the forest sector are grouped into four general categories: • maintaining or increasing the forest area through reduction of deforestation and degradation and through afforestation/ reforestation; • maintaining or increasing the stand-level carbon density (tonnes of carbon per ha) through the reduction of forest degradation and through planting, site preparation, tree improvement, fertilization, uneven-aged stand management, or other appropriate silviculture techniques; • maintaining or increasing the landscape-level carbon density using forest conservation, longer forest rotations, fire management, and protection against insects; • increasing off-site carbon stocks in wood products and enhancing product and fuel substitution using forest-derived biomass to substitute products with high fossil fuel requirements, and increasing the use of biomass-derived energy to substitute fossil fuels. Each mitigation activity has a characteristic time sequence of actions, carbon benefits and costs (Figure 9.4). Relative to a baseline, the largest short-term gains are always achieved through mitigation activities aimed at emission avoidance (e.g., reduced deforestation or degradation, fire protection, and slash burning). But once an emission has been avoided, carbon stocks on that forest will merely be maintained or increased slightly. In contrast, the benefits from afforestation accumulate over years to decades but require up-front action and expenses. Most forest management activities aimed at enhancing sinks require up-front investments. The duration and magnitude of their carbon benefits differ by region, type of action and initial condition of the forest. In the long term, sustainable forest management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual yield of timber, fibre, or energy from the forest, will generate the largest sustained mitigation benefit. Reduction in fossil fuel use in forest management activities, forest nursery operations, transportation and industrial production provides additional opportunities similar to those in other sectors, but are not discussed here (e.g., see Chapter 5, Transportation). The options available in agro-forestry systems are conceptually similar to those in other parts of the forest sector and in the agricultural sector (e.g., non-CO2 GHG emission management). Mitigation using urban forestry includes increasing the carbon density in settlements, but indirect effects must also be evaluated, such as reducing heating and cooling energy use in houses and office buildings, and changing the albedo of paved parking lots and roads. 9.4.2
Land-use sector
Forest sector
Description of mitigation measures
Services used by society
Figure 9.3: Forest sector mitigation strategies need to be assessed with regard to their impacts on carbon storage in forest ecosystems on sustainable harvest rates and on net GHG emissions across all sectors.
Each of the mitigation activities is briefly described. The development of a portfolio of forest mitigation activities requires
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societal needs. Reduced deforestation and degradation is the forest mitigation option with the largest and most immediate carbon stock impact in the short term per ha and per year globally (see Section 9.2 and global mitigation assessments below), because large carbon stocks (about 350-900 tCO2/ha) are not emitted when deforestation is prevented. The mitigation costs of reduced deforestation depend on the cause of deforestation (timber or fuelwood extraction, conversion to agriculture, settlement, or infrastructure), the associated returns from the non-forest land use, the returns from potential alternative forest uses, and on any compensation paid to the individual or institutional landowner to change land-use practices. These costs vary by country and region (Sathaye et al., 2007), as discussed below. 9.4.2.2
Figure 9.4: Generalized summary of forest sector options and type and timing of effects on carbon stocks and the timing of costs 3
an understanding of the magnitude and temporal dynamics of the carbon benefits and the associated costs. 9.4.2.1
Maintaining or increasing forest area: reducing deforestation and degradation
Deforestation - human-induced conversion of forest to nonforest land uses - is typically associated with large immediate reductions in forest carbon stock, through land clearing. Forest degradation - reduction in forest biomass through nonsustainable harvest or land-use practices - can also result in substantial reductions of forest carbon stocks from selective logging, fire and other anthropogenic disturbances, and fuelwood collection (Asner et al., 2005). In some circumstances, deforestation and degradation can be delayed or reduced through complete protection of forests (Soares-Filho et al., 2006), sustainable forest management policies and practices, or by providing economic returns from non-timber forest products and forest uses not involving tree removal (e.g., tourism). Protecting forest from all harvest typically results in maintained or increased forest carbon stocks, but also reduces the wood and land supply to meet other
3
We thank Mike Apps for a draft of this figure.
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Maintaining or increasing forest area: afforestation/reforestation
Afforestation and reforestation are the direct human-induced conversion of non-forest to forest land through planting, seeding, and/or the human-induced promotion of natural seed sources. The two terms are distinguished by how long the nonforest condition has prevailed. For the remainder of this chapter, afforestation is used to imply either afforestation or reforestation. To date, carbon sequestration has rarely been the primary driver of afforestation, but future changes in carbon valuation could result in large increases in the rates of afforestation (US EPA, 2005). Afforestation typically leads to increases in biomass and dead organic matter carbon pools, and to a lesser extent, in soil carbon pools, whose small, slow increases are often hard to detect within the uncertainty ranges (Paul et al., 2003). Biomass clearing and site preparation prior to afforestation may lead to short-term carbon losses on that site. On sites with low initial soil carbon stocks (e.g., after prolonged cultivation), afforestation can yield considerable soil carbon accumulation rates (e.g., Post and Kwon (2000) report rates of 1 to 1.5 t CO2/ yr). Conversely, on sites with high initial soil carbon stocks, (e.g., some grassland ecosystems) soil carbon stocks can decline following afforestation (e.g., Tate et al. (2005) report that in the whole of New Zealand soil carbon losses amount up to 2.2 MtCO2/yr after afforestation). Once harvesting of afforested land commences, forest biomass carbon is transferred into wood products that store carbon for years to many decades. Accumulation of carbon in biomass after afforestation varies greatly by tree species and site, and ranges globally between 1 and 35 t CO2/ha.yr (Richards and Stokes, 2004). Afforestation costs vary by land type and region and are affected by the costs of available land, site preparation, and labour. The cost of forest mitigation projects rises significantly
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when opportunity costs of land are taken into account (VanKooten et al., 2004). A major economic constraint to afforestation is the high initial investment to establish new stands coupled with the several-decade delay until afforested areas generate revenue. The non-carbon benefits of afforestation, such as reduction in erosion or non-consumptive use of forests, however, can more than off-set afforestation cost (Richards and Stokes, 2004).
wooden frames instead of concrete frames reduces lifecycle net carbon emissions by 110 to 470 kg CO2 per square metre of floor area (Gustavsson and Sathre, 2006). The mitigation benefit is greater if wood is first used to replace concrete building material and then after disposal, as biofuel.
9.4.2.3
For quantification of the economic potential of future mitigation by forests, three approaches are presented in current literature. These are: a) regional bottom-up assessments per country or continent; b) global forest sector models; and c) global multi-sectoral models. An overview of studies for these approaches is presented in Section 9.4.3. The final integrated global conclusion and regional comparison is given in Section 9.4.4. Supply of forest biomass for bioenergy is given in Box 9.2 and incorporated in Section 11.3.1.4, within the energy sector’s mitigation potential. For comments on the baselines, see Section 9.3.
Forest management to increase stand- and landscape-level carbon density
Forest management activities to increase stand-level forest carbon stocks include harvest systems that maintain partial forest cover, minimize losses of dead organic matter (including slash) or soil carbon by reducing soil erosion, and by avoiding slash burning and other high-emission activities. Planting after harvest or natural disturbances accelerates tree growth and reduces carbon losses relative to natural regeneration. Economic considerations are typically the main constraint, because retaining additional carbon on site delays revenues from harvest. The potential benefits of carbon sequestration can be diminished where increased use of fertilizer causes greater N2O emissions. Drainage of forest soils, and specifically of peatlands, may lead to substantial carbon loss due to enhanced respiration (Ikkonen et al., 2001). Moderate drainage, however, can lead to increased peat carbon accumulation (Minkkinen et al., 2002). Landscape-level carbon stock changes are the sum of standlevel changes, and the impacts of forest management on carbon stocks ultimately need to be evaluated at landscape level. Increasing harvest rotation lengths will increase some carbon pools (e.g., tree boles) and decrease others (e.g., harvested wood products (Kurz et al., 1998).
9.4.3
9.4.3.1
Global assessments
Regional bottom-up assessments
Regional assessments comprise a variety of model results. On the one hand, these assessments are able to take into account the detailed regional specific constraints (in terms of ecological constraints, but also in terms of land owner behaviour and institutional frame).On the other hand, they also vary in assumptions, type of potential addressed, options taken into account, econometrics applied (if any), and the adoption of baselines. Thus, these assessments may have strengths, but when comparing and summing up, they have weaknesses as well. Some of these assessments, by taking into account institutional barriers, are close to a market potential. Tropics
9.4.2.4
Increasing off-site carbon stocks in wood products and enhancing product and fuel substitution
Wood products derived from sustainably managed forests address the issue of saturation of forest carbon stocks. The annual harvest can be set equal to or below the annual forest increment, thus allowing forest carbon stocks to be maintained or to increase while providing an annual carbon flow to meet society’s needs of fibre, timber and energy. The duration of carbon storage in wood products ranges from days (biofuels) to centuries (e.g., houses and furniture). Large accumulations of wood products have occurred in landfills (Micales and Skog, 1997). When used to displace fossil fuels, woodfuels can provide sustained carbon benefits, and constitute a large mitigation option (see Box 9.2). Wood products can displace more fossil-fuel intensive construction materials such as concrete, steel, aluminium, and plastics, which can result in significant emission reductions (Petersen and Solberg, 2002). Research from Sweden and Finland suggests that constructing apartment buildings with
The available studies about mitigation options differ widely in basic assumptions regarding carbon accounting, costs, land areas, baselines, and other major parameters. The type of mitigation options considered and the time frame of the study affect the total mitigation potential estimated for the tropics. A thorough comparative analysis is, therefore, very difficult. More detailed estimates of economic or market potential for mitigation options by region or country are needed to enable policy makers to make realistic estimates of mitigation potential under various policy, carbon price, and mitigation program eligibility rule scenarios. Examples to build on include BenitezPonce et al. (2007) and Waterloo et al. (2003), highlighting the large potential by avoiding deforestation and enhancing afforestation and reforestation, including bioenergy. Reducing deforestation Assumptions of future deforestation rates are key factors in estimates of GHG emissions from forest lands and of mitigation benefits, and vary significantly across studies. In all the studies, 551
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however, future deforestation is estimated to remain high in the tropics in the short and medium term. Sathaye et al. (2007) estimate that deforestation rates continue in all regions, particularly at high rates in Africa and South America, for a total of just under 600 million ha lost cumulatively by 2050. Using a spatial-explicit model coupled with demographic and economic databases, Soares-Filo et al. (2006) predict that, under a business-as-usual scenario, by 2050, projected deforestation trends will eliminate 40% of the current 540 million ha of Amazon forests, releasing approximately 117,000 ± 30,000 MtCO2 of carbon to the atmosphere (Box 9.1). Reducing deforestation is, thus, a high-priority mitigation option within tropical regions. In addition to the significant carbon gains, substantive environmental and other benefits could be obtained from this option. Successfully implementing mitigation activities to counteract the accelerated loss of tropical forests requires understanding the causes for deforestation, which are multiple and locally based; few generalizations are possible (Chomitz et al., 2006). Recent studies have been conducted at the national, regional, and global scale to estimate the mitigation potential (areas, carbon benefits and costs) of reducing tropical deforestation. In a short-term context (2008-2012), Jung (2005) estimates that 93% of the total mitigation potential in the tropics corresponds to avoided deforestation. For the Amazon basin, Soares- Filo et al. (2006) estimate that by 2050 the cumulative avoided deforestation potential for this region reaches 62,000 MtCO2 under a “governance” scenario (see Box 9.1). Looking at the long-term, (Sohngen and Sedjo, 2006) estimate that for 27.2 US$/tCO2, deforestation could potentially be virtually eliminated. Over 50 years, this could mean a net cumulative gain of 278,000 MtCO2 relative to the baseline and
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Carbon price Figure 9.5: Cumulative carbon gained through avoided deforestation by 2055 over the reference case, by tropical regions under various carbon price scenarios
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In a study of eight tropical countries covering half of the total forested area, Grieg-Gran (2004) present a best estimate of total costs of avoided deforestation in the form of the net present value of returns from land uses that are prevented, at 5 billion US$ per year. These figures represent costs of 483 US$ to 1050 US$/ha. Afforestation and reforestation The assumed land availability for afforestation options depends on the price of carbon and how that competes with existing or other land-use financial returns, barriers to changing land uses, land tenure patterns and legal status, commodity price support, and other social and policy factors. Cost estimates for carbon sequestration projects for different regions compiled by Cacho et al., (2003) and by Richards and Stokes (2004) show a wide range. The cost is in the range of 0.5 US$ to 7 US$/tCO2 for forestry projects in developing countries, compared to 1.4 US$ to 22 US$/tCO2 for forestry projects in industrialized countries. In the short-term (20082012), an estimate of economic potential area available for afforestation/ reforestation under the Clean Development Mechanism (CDM) is estimated to be 5.3 million ha in Africa, Asia and Latin America together, with Asia accounting for 4.4 million ha (Waterloo et al., 2003). Summing the measures, the cumulative carbon mitigation benefits (Figure 9.6) by 2050 for a scenario of 2.7 US$/ tCO2 + 5% annual carbon price increment for one model are estimated to be 91,400 MtCO2; 59% of it coming from avoided deforestation. These estimates increase for a higher price scenario of 5.4 US$/tCO2 + 3%/yr annual carbon price into 104,800 MtCO2), where 69% of total mitigation comes from avoiding deforestation (Sathaye et al., 2007). During the period 2000-2050, avoided deforestation in South America and Asia dominate by accounting for 49% and 21%, respectively, of the total mitigation potential. When afforestation is considered, Asia dominates. The mitigation potential of the continents Asia, Africa and Latin America dominates the global total mitigation potential for the period up to 2050 and 2100, respectively (Figure 9.6).
Gt CO2
Source: Sohngen and Sedjo, 2006.
422 million additional hectares in forests. For lower prices of 1.36 US$/tCO2, only about 18,000 MtCO2 additional could be sequestered over 50 years. The largest gains in carbon would occur in Southeast Asia, which gains nearly 109,000 MtCO2 for 27.2 US$/tCO2, followed by South America, Africa, and Central America, which would gain 80,000, 70,000, and 22,000 MtCO2 for 27.2 US$/tCO2, respectively (Figure 9.5).
In conclusion, the studies report a large variety for mitigation potential in the tropics. All studies indicate that this part of the world has the largest mitigation potential in the forestry sector. For the tropics, the mitigation estimates for lower price ranges (<20 US$/tCO2) are around 1100 MtCO2/yr in 2040, about
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half of this potential is located in Central and South America (Sathaye et al., 2007; Soares Filho et al., 2006; Sohngen and Sedjo, 2006). For each of the regions Africa and Southeast Asia, this mitigation potential is estimated at 300 MtCO2/yr in 2040. In the high range of price scenarios (< 100 US$/tCO2), the mitigation estimates are in the range of 3000 to 4000MtCO2/yr in 2040. In the summary overviews in Section 9.4.4, an average estimate of 3500 is used, with the same division over regions: 875, 1750 and 875 for Africa, Latin and South America, and Southeast Asia, respectively. The global economic potential for the tropics ranges from 1100 to 3500 MtCO2/yr in 2040 (Table 9.6). OECD North America
50
avoided deforestation Africa
0 2000-2050
2000-2100
Figure 9.6: Cumulative mitigation potential (2000-2050 and 2000-2100) according to mitigation options under the 2.7 US$/tCO2 +5%/yr annual carbon price increment Source: Sathaye et al., 2007.
Figure 9.8 shows the technical potential of management actions aimed at modifying the net carbon balance in Canadian forests (Chen et al., 2000). Of the four scenarios examined, the potential was largest in the scenario aimed at reducing regeneration delays by reforesting after natural disturbances. The second largest estimate was obtained with annual, largescale (125 million ha) low-intensity (5 kg N/ha/yr) nitrogen fertilization programmes. Neither of these scenarios is realistic,
Box 9.1 Deforestation scenarios for the Amazon Basin An empirically based, policy-sensitive simulation model of deforestation for the Pan-Amazon basin has been developed (Soares-Filho et al., 2006) (Figure 9.7). Model output for the worst-case scenario (business-as-usual) shows that, by 2050, projected deforestation trends will eliminate 40% of the current 5.4 million km2 of Amazon forests, releasing approximately 117,000 MtCO2 cumulatively by 2050. Conversely, under the best-case governance scenario, 4.5 million km2 of forest would remain in 2050, which is 83% of the current extent or only 17% deforested, reducing cumulative carbon emissions by 2050 to only 55,000 MtCO2. Current experiments in forest conservation on private properties, markets for ecosystem services, and agro-ecological zoning must be refined and implemented to achieve comprehensive conservation. Part of the financial resources needed for these conservation initiatives could come in the form of carbon credits resulting from the avoidance of 62,000 MtCO2 emissions over 50 years. 500
Gt CO2
400 Pan Amazon
300 200
Brazilian Amazon
100 0
un de Cu r m G ul ov at er ive na E nc m e iss by io 20 ns 50
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n
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C um un ula de tiv rB eE AU mi s by sio 20 ns 50
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Figure 9.7: Current carbon stocks for the Pan-Amazon and Brazilian Amazon (left bar) and estimates of cumulative future emission by 2050 from deforestation under BAU (business-as-usual) and governance scenarios. Note: The difference between the two scenarios represents an amount equivalent to eight times the carbon emission reduction to be achieved during the first commitment period of the Kyoto Protocol.
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Agricultural CH4 and N2O mitigation Forest management
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Figure 9.8: OECD North America: technical potential for the forest sector alone for Canada (left, sink is positive) and the economic potential (at 15 US$/tCO2eq in constant real prices) in the agriculture and forestry sector in the USA (right) Left: Chen et al., 2000; right: US-EPA, 2005
however, but can be seen as indications of the type of measures and impact on carbon balance (as described by Chen et al., 2000). Chen’s measures sum up to a technical potential of 570 MtCO2/yr. Based on the assumption that the economic potential is about 10% of technical potential (see Section 9.4.3.3. for carbon prices 20 US$/tCO2), the economic potential can be “guesstimated” at around 50-70 MtCO2/yr (Table 9.6). Other studies have explored the potential of large-scale afforestation in Canada. Mc Kenney et al. (2004) project that at a carbon price of 25 US$/tCO2, 7.5 million ha of agricultural land would become economically attractive for poplar plantations. Economic constraints are contributing to the declining trend in afforestation rates in Canada from about 10,000 ha/yr in 1990 to 4,000 ha/yr in 2002 (White and Kurz, 2005). For the USA, Richards and Stokes (2004) reviewed eight national estimates of forest mitigation and found that carbon prices ranging from 1 to 41 US$/tCO2 generated an economic mitigation potential of 47-2,340 MtCO2/yr from afforestation, 404 MtCO2 from forest management, and 551-2,753 MtCO2/yr from total forest carbon. Sohngen and Mendelsohn (2003) found that a carbon programme with prices rising from 2 US$/tCO2 to 51 US$/tCO2 during this century could induce sequestration of 122 to 306 MtCO2/yr total carbon sequestration, annualized over a 100-year time frame.
Europe Most assessments shown (Figure 9.9) are of the carbon balance of the forest sector of Europe’s managed forest as a whole4. Additional effects of measures were studied by Cannell (2003), Benitez-Ponce et al. (2007), EEA (2005), and Eggers et al. (2007). Karjalainen et al, (2003) present a projection of the full sector carbon balance (Figure 9.9). Eggers et al. (2007) presents the European forest sector carbon sink under two global SRES scenarios, and a maximum difference between scenarios of 197 MtCO2/yr in 2040. Therefore, an additionally achievable sink of 90 to 180 MtCO2/yr was estimated (Table 9.6). Economic analyses were not only done; country studies were done, for example, Hoen and Solberg (1994) for Norway. New European scale economic analyses may be available from the INSEA5 project, MEACAP project6, and Carbo Europe 7. Issues in European forestry where mitigation options can be found include: afforestation of abandoned agricultural 500 Mt CO2
4 5 6 7
Europe here excludes the European part of Russia. www.iiasa.ac.at/Research/FOR/INSEA/index.html?sb=19 www.ieep.eu/projectMiniSites/meacap/index.php www.carboeurope.org/
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IMAGE reference case (Brinkman, 2005)
400 Karjalainen et al., (2003)
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US EPA (2005) present that, at 15 US$/tCO2, the mitigation potential of afforestation and forest management (annualized) would amount to 356 MtCO2/yr over a 100-year time frame. At 30 US$/tCO2, this analysis would generate 749 MtCO2 annualized over 100 years. At higher prices and in the long term, the potential was mainly determined by biofuels. With the mitigation potential given above for Canada, the OECD North America sums to a range of 400 to 820 MtCO2/yr in 2040 (Table 9.6).
Liski and Kauppi (2001)
Cannell (2003)
historic (Nabuurs et al., 2003)
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Figure 9.9: European forest sector carbon sink projections for which various assumptions on implementation rate of measures were made Note: positive = sink.
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plantations to model a carbon account for Australia’s post-1990 plantation estate. The annual sequestration rate in forests and wood products together is estimated to reach 20 MtCO2/yr in 2020.
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2.6 IMAGE reference case (Brinkman, 2005)
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Figure 9.10: Russian Federation forest sector carbon sink projections, with assumptions regarding implementation rates differing in the various studies Note: positive = sink.
lands; bioenergy from complementary fellings; and forest management practices to address carbon saturation in older forests. Furthermore, management of small now under-managed woodlands represent a potential (Viner et al., 2006) and also in combination with adaptation measures in connecting the fragmented nature reserves (Schröter et al., 2005). Russian Federation The forests of the Russian Federation include large areas of primary (mostly boreal) forests. Most estimates indicate that the Russian forests are neither a large sink nor a large source. Natural disturbances (fire) play a major role in the carbon balance with emissions up to 1,600 MtCO2/yr (Zhang et al., 2003). Large uncertainty surrounds the estimates for the current carbon balance ((Shvidenko and Nilsson et al., 2003). For the decade 1990-2000, the range of carbon sink values for Russia is 350-750 MtCO2/yr (Nilsson et al., 2003; Izrael et al., 2002). A recent analysis estimated the net sink in Russia at 146-439 MtCO2/yr at present (Sohngen et al., 2005). They projected this baseline to be about 257 MtCO2 per year in 2010, declining to a net source by 2030 as younger forests mature and are harvested. They estimated the economic potential in Russia of afforestation and reforestation at 73-124 MtCO2/yr on average over an 80-year period, for a carbon price of 1.9-3.55 US$/ tCO2, and 308-476 MtCO2/yr at prices of more than 27 US$/ tCO2 (Figure 9.10). Based on these estimates, the estimated economic mitigation potential would be between 150 and 300 MtCO2/yr in the year 2040 (Table 9.6). OECD Pacific Richards and Brack (2004) used estimates of establishment rates for hardwood (short and long rotation) and softwood
New Zealand reached a peak in new planting of around 98,000 ha in 1994 and estimates of stock changes largely depend on afforestation rates (MfE, 2002). If a new planting was maintained at 40,000 ha/yr, the stock increase in forests established since 1990 (117 MtCO2 cumulative since 1990) is estimated to offset all increases in emissions in New Zealand since 1990. The total stock increase in all forests would offset all emissions increases until 2020. However, the current new planting rate has declined to 6,000 ha and conversion of 7,000 ha of plantations to pasture has led to net deforestation in the year to March 2005 (MAF, 2006). As a result, the total removal units anticipated to be available during the first commitment period dropped to 56 MtCO2 in 2005 (MfE, 2005). Trotter et al. (2005) estimate New Zealand has approximately 1.45 million ha of marginal pastoral land suitable for afforestation. If all of this area was established, total sequestration could range from 10 to 42 MtCO2/yr. This would lead to a removal of approximately 44 to 170 MtCO2 cumulative by 2010 at 13 US$/tCO2. In Japan, 67% of the land is covered with forests including semi-natural broad-leaved forests and planted coniferous forests mostly. The sequestration potential is estimated in the range of 35 to 70 MtCO2/yr (Matsumoto et al., 2002; Fang et al., 2005), and planted forests account for more than 60% of the carbon sequestration. These assessments show that there is little potential for afforestation and reforestation, while forest management and practices for planted forests including thinning and regeneration are necessary to maintain carbon sequestration and to curb saturation. In addition, there seems to be large potential for bioenergy as a mitigation option. These three countries for the region lead to an estimate of potential in the range of 85 to 255 MtCO2/yr in 2040 (Table 9.6). Non-annex I East Asia East Asia to a large extent formed by China, Korea, and Mongolia has a range of forest covers from a relatively small area of moist tropical forest to large extents of temperate forest and steppe-like shrubland. Country assessments for the forest sector all project a sink ranging from 75 to 400 MtCO2/ yr (Zhang and Xu, 2003). Given the large areas and the fast economic development (and thus demand for wood products resulting in increased planting), the additional potential in the region would be in the high range of the country assessments at 150 to 400 MtCO2/yr (Table 9.6). Issues in forestry with which the carbon sequestration goal can be combined sustainably are: reducing degradation of tropical and dry woodlands; halting 555
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desertification of the steppes (see Chapter 8); afforestation; and bioenergy from complementary fellings. 9.4.3.2
Global Forest sectoral modelling
Currently, no integrated assessment (Section 9.4.3.3) and climate stabilization economic models (Section 3.3.5) have fully integrated a land use sector with other sectors in the models. Researchers have taken several approaches, however, to account for carbon sequestration in integrated assessment models, either by iterating with the land sector models (e.g., Sohngen and Mendelsohn, 2003), or implementing mitigation response curves generated by the sectoral model (Jakeman and Fisher, 2006). The sectoral model results described here use exogenous carbon price paths to simulate effects of different climate policies and assumptions. The starting point and rate of increase are determined by factors such as the aggressiveness of the abatement policy, abatement option and cost assumptions, and the social discount rate (Sohngen and Sedjo, 2006). Since TAR, several new global assessments of forest mitigation potential have been produced. These include BenitezPonce et al, (2004; 2007), Waterloo et al. (2003) with a constraints study, Sathaye et al. (2007), Strengers et al. (2007) Vuuren et al. (2007), and Riahi et al. (2006). Global estimates are provided that are consistent in methodology across countries and regions, and in terms of measures included. Furthermore, they provide a picture in which the forestry sector is one option that is part of a multi sectoral climate policy and its measures. Thus, these assessments provide insight into whether landbased mitigation is a cost-efficient measure in comparison to other mitigation efforts. Some of these models use a grid-based global land-use model and provide insight into where these models allocate the required afforestation (Figure 9.11). The IMAGE model (Strengers et al., 2007) allocates bioenergy plantations and carbon plantations mostly in the fringes of the large forest biomes, and in Eastern Europe. The Waterloo study only looked at tropical countries, but found by far the largest potential in China and Brazil. Several models report at the regional level, and project strong avoided deforestation in Africa, the Amazon, and to a lesser extent in Southeast Asia (where land opportunity costs in the timber market are relatively high). Benitez-Ponce (2004) maps geographic distribution of afforestation, adjusted by country risk estimates, under a 50
Figure 9.11: Comparison of allocation of global afforestation in various studies (A) Location of bioenergy and carbon plantations (B) Additional sequestration from afforestation per tropical country per year in the period 2008-2012 (MtC/yr), (C) Percentage of a grid cell afforested (D) Cumulative carbon sequestration through afforestation between 2000 and 2012 in Central and South America). Source: (A) Strengers et al., 2007; (B) Waterloo et al., 2003; (C) Strengers et al., 2007; (D) Benitez-Ponce et al., 2007.
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US$/t carbon price. Afforestation activity is clustered in bands in South-Eastern USA, Southeast Brazil and Northern South America, West Africa, north of Botswana and East Africa, the steppe zone grasslands from Ukraine through European Russia, North- Eastern China, and parts of India, Southeast Asia, and Northern Australia. Hence, forest mitigation is likely to be patchy, but predictable using an overlay of land characteristics, land rental rates, and opportunity costs, risks, and infrastructure capacity. Several models produced roughly comparable assessments for a set of constant and rising carbon price scenarios in the EMF 21 modelling exercise, from 1.4 US$/tCO2 in 2010 and, rising by 5% per year to 2100, to a 27 US$ constant CO2 price, to 20 US$/tCO2 rising by 1.4 US$/yr though 2050 then capped. This exercise allowed more direct comparison of modelling assumptions than usual. Caveats include: (1) models have varying assumptions about deforestation rates over time, land area in forest in 2000 and beyond, and land available for mitigation; and (2) models have different drivers of land use change (e.g., population and GDP growth for IMAGE, versus land rental rates and timber market demand for GTM). Global models provide broad trends, but less detail than national or project analyses. Generally global models do not address implementation issues such as transaction costs (likely to vary across activities, regions), barriers, and mitigation programme rules, which tend to drive mitigation potential downward toward true market potential. Political and financial risks in implementing afforestation and reforestation by country were considered by Benitez-Ponce et al. (2007), for example, who found that the sequestration reduced by 59% once the risks were incorporated. In the last few years, more insight has been gained into carbon supply curves. At a price of 5 US$/tCO2, Sathaye et al. (2007) project a cumulative carbon gain of 10,400 MtCO2 by 2050 (Figure 9.12b). The mitigation results from a combination of avoided deforestation (68%) and afforestation (32%). These results are typical in their very high fraction of mitigation from reduced deforestation. Sohngen and Sedjo (2006) estimate some 80% of carbon benefits in some scenarios from land-use change (e.g., reduced deforestation and afforestation/reforestation) versus some 20% from forest management. Benitez-Ponce et al. (2007) project that at a price of 13.6 US$/tCO2, the annual sequestration from afforestation and reforestation for the first 20 years amounts to on average 510 MtCO2/yr (Figure 9.12a). For the first 40 years, the average annual sequestration is 805 MtCO2/yr. The single price of 13.6 US$/tCO2 used by Benitez-Ponce et al. (2005) should make afforestation an attractive land-use option in many countries. It covers the range of median values for sequestration costs that Richards and Stokes (2004) give of 1 US$ to 12 US$/tCO2, although VanKooten et al. (2004) present marginal cost results rising far higher. Sathaye et al. (2007) project the economic
Forestry
potential cumulative carbon gains from afforestation and avoided deforestation together (see also tropics, Section 9.4.3.1.). In the moderate carbon price scenarios, the cumulative carbon gains by 2050 add up to 91,400 to 104,800 MtCO2. The anticipated carbon price path over time has important implications for forest abatement potential and timing. Rising carbon prices provide an incentive for delaying forest abatement actions to later decades, when it is more profitable (Sohngen and Sedjo, 2006). Carbon price expectations influence forest investment decisions and are, therefore, an important consideration for estimating mitigation potential. Contrary, high constant carbon prices generate significant early mitigation, but the quantity may vary over time. Mitigation strategies need to take into account this temporal dimension if they seek to meet specific mitigation goals at given dates in the future (US EPA, 2005). Some patterns emerge from the range of estimates reviewed in order to assess the ratio between economic potential and technical potential (Sathaye et al., 2007; Lewandrowski et al., 2004; US EPA, 2005; Richards and Stokes, 2004). The technical potential estimates are generally significantly larger than the economic potential. These studies are difficult to compare, since each estimate uses different assumptions by different analysts. Economic models used for these analyses can generate mitigation potential estimates in competition to other forestry or agricultural sector mitigation options. Generally, they do not specify or account for specific policies and measures and market penetration rates, so few market potential estimates are generated. Many studies do not clearly state which potentials are estimated. The range of economic potential as a percentage of technical potential is 2% to 100% (the latter against all costs). At carbon prices less than 7 US$/tCO2, the highest estimate of economic potential is 16% of the technical potential. At carbon prices from 27 US$/tCO2 to 50 US$/tCO2, the range of economic potential is estimated to be 58% or higher of the technical potential, a much higher fraction as carbon prices rise. Table 9.3 summarizes mitigation results for four major global forest analyses for a single near-term date of 2030: two forest sector models - GTM (Sohngen and Sedjo, 2006; and GCOMAP (Sathaye et al., 2007), one recent detailed spatially resolved analysis of afforestation (Benitez-Ponce et al., 2007), and one integrated assessment model with detail for the forest sector (IMAGE 2.2, Vuuren et al., 2007). These studies offer roughly comparable results, including global coverage of the forest sector, and land-use competition across at least two forest mitigation options (except Benitez-Ponce et al., 2007). All but the Benitez-Ponce et al. study have been compared by the modelling teams in the EMF 21 modelling exercise (see Sections 3.2.2.3 and 3.3.5) as well. These global models (Table 9.3) present a large potential for climate mitigation through forestry activities. The global annual 557
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A Cumulative carbon (Gt CO2)
180
27 US$/tCO2
160
13.6 US$/tCO2
140
8 US$/tCO2
120
5.5 US$/tCO2
100 80 60 40 20 0 0
20
40
60
80
100
year B
C
1000
US$95/tC
800
250
US$/tCO2
2010
200
2025
Temperate/Boreal
2050
600
150
2075
Tropics
2100
400
100 Global sequestration
200
0 0
50 0 0.5
1
1.5
2
GtC/yr
0
2
4
6
8
10
12
14
Gt CO2/yr (annual equivalent amount, r=0.05)
Figure 9.12: Comparison of carbon supply curves globally from various studies (A) Cumulative carbon supply curves: afforestation and reforestation by year and price scenario. At a price of 100 US$/tC after 70 years, some 40 Gt carbon will have been supplied cumulatively from afforestation. (B) Annual cost-supply curves for abandoned agricultural land in the B2 scenario. For example, at a price of 100 US$/tC, in 2075, some 250 Mt carbon will have been supplied annually from afforestation and reducing deforestation. (C) Annual marginal cost curves for carbon sequestration in forests: estimates for boreal, temperate, and tropical regions. For example, at a price of 100 US$/tC, some 1400 Mt carbon will have been supplied annually from afforestation and reducing deforestation in 2100. Sources: (A) Benitez-Ponce et al., 2005; (B) Strengers et al., 2007; (C) Sohngen and Sedjo, 2006.
potential in 2030 is estimated at 13,775 MtCO2/yr (at carbon prices less than or equal to 100 US$/tCO2), 36% (~5000 MtCO2/ yr) of which can be achieved under a price of 20 US$/tCO2. Reduced deforestation in Central and South America is the most important measure in a single region with 1,845 MtCO2/yr. The total for the region is the largest for Central and South America with an estimated total potential of 3,100 MtCO2/yr. Regions with a second largest potential, each around 2000 MtCO2, are
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Africa, Centrally Planned Asia, other Asia, and USA. These results project significantly higher mitigation than the regional largely bottom-up results. This is somewhat surprising, and likely, the result of the modelling structure, assumptions, and which activities are included. Additional research is required to resolve the various estimates to date using different modelling approaches of the potential magnitude of forestry mitigation of climate change.
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Forestry
Table 9.3: Potential of mitigation measures of global forestry activities. Global model results indicate annual amount sequestered or emissions avoided, above business as usual, in 2030 for carbon prices 100 US$/tCO2 and less.
Region
Activity
USA
Afforestation Reduced deforestation
Europe
0.3
TOTAL
2,045
0.26
0.31
115
0.31
0.24
Afforestation
10
0.17
0.27
170
0.3
0.19
TOTAL
295
0.3
0.21
Afforestation
115
0.24
0.37
30
0.48
0.25
Forest management
110
0.2
0.35
TOTAL
255
0.25
0.34
Afforestation
605
0.26
0.26
110
0.35
0.29
Forest management
1,200
0.25
0.28
TOTAL
1,915
0.26
0.27
545
0.35
0.3
Afforestation
85
0.37
0.22
Forest management
1,055
0.32
0.27
TOTAL
1,685
0.33
0.28
750
0.39
0.33
1,845
0.47
0.37
550
0.43
0.35
3,145
0.44
0.36
0.7
0.16
Afforestation
TOTAL Afforestation Reduced deforestation Forest management TOTAL
1,160 100 1,925
0.7
0.19
0.65
0.19
0.7
0.18
745
0.39
0.31
Reduced deforestation
670
0.52
0.23
Forest management
960
0.54
0.19
2,375
0.49
0.24
Afforestation
60
0.5
0.26
Reduced deforestation
30
0.78
0.11
Forest management
45
0.5
0.25
135
TOTAL TOTAL
665
Afforestation
TOTAL Middle East
10
Forest management
Forest management
Other Asia
0.3
0.32
Reduced deforestation
Africa
0.3 0.2
Reduced deforestation
Central and South America
445
0.26
Reduced deforestation
Countries in transition
Fraction in cost class: 20-50 US$/tCO2
1,590
Reduced deforestation
Non-annex I East Asia
Fraction in cost class: 1-20 US$/tCO2
Forest management
Reduced deforestation
OECD Pacific
Potential at costs equal or less than 100 US$/tCO2 , in MtCO2/yr in 2030 1)
0.57
0.22
Afforestation
4,045
0.4
0.28
Reduced deforestation
3,950
0.54
0.28
Forest management
5,780
0.34
0.28
13,775
0.42
0.28
TOTAL
1) Results average activity estimates reported from three global forest sector models including GTM (Sohngen and Sedjo, 2006), GCOMAP (Sathaye et al., 2007), and IIASA-DIMA (Benitez-Ponce et al., 2007). For each model, output for different price scenarios has been published. The original authors were asked to provide data on carbon supply under various carbon prices. These were summed and resulted in the total carbon supply as given middle column above. Because carbon supply under various price scenarios was requested, fractionation was possible as well. Two right columns represent the proportion available in the given cost class. None of the models reported mitigation available at negative costs. The column for the carbon supply fraction at costs between 50 and 100 US$/tCO2 can easily be derived as 1- sum of the two right hand columns.
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9.4.3.3 Global forest mitigation in climate stabilization analysis Evaluating the cost-competitiveness of forestry mitigation versus other sector options in achieving climate mitigation goals requires different modelling capabilities. Global integrated assessment and climate economic models are top-down models, generally capable of dynamically representing feedbacks in the economy across sectors and regions and reallocations of inputs, as well as interactions between economic and atmosphericocean-terrestrial systems. These models can be used to evaluate long-term climate stabilization scenarios, like achieving a stabilization target of 450 or 650 CO2-eq by 2100 (see Section 3.3.5). In this framework, the competitive mitigation role of forest abatement options, such as afforestation, can be estimated as part of a dynamic portfolio of the least-cost combination of mitigation options from across all sectors of the economy, including energy, transportation, and agriculture. To date, researchers have used various approaches to represent terrestrial carbon sequestration in integrated assessment models. These approaches include iterating with the land-sector models (e.g., Sohngen and Mendelsohn, 2003), and implementing mitigation response curves generated by a sectoral model (Jakeman and Fisher, 2006). At present, all integrated assessment models include afforestation strategies, but only some consider avoided deforestation, and none explicitly model forest management mitigation options (e.g., harvest timing: Rose et al., 2007). However, the top-down mitigation estimates account for economic feedbacks, as well as for some biophysical feedbacks such as climate and CO2 fertilization effects on forest growth.
Table 9.4: Global forest cost-effective mitigation potential in 2030 from climate stabilization scenarios, or 450-650 CO2-eq atmospheric concentration targets, produced by top-down global integrated assessment models. Forest options are in competition with other sectoral options to generate least-cost mitigation portfolios for achieving long-run stabilization. Carbon price in scenario (US$/tCO2-eq)
Mitigation potential in 2030 MtCO2-eq/yr
Number of scenario results
0 - 20
40 - 970
4
20 - 50
604 - 790
3
50 - 100
nd
0
>100
851
1
Notes: Jakeman and Fisher (2006) estimated 2030 forest mitigation of 3,059 MtCO2, well above other estimates, but not included due to an inconsistency inflating their forest mitigation estimates for the early 21st century. nd = no data.
Source: Section 3.3.5; data from Rose et al., 2007.
The few estimates of global competitive mitigation potential of forestry in climate stabilization in 2030 are given in Table 9.4. Some estimates represent carbon plantation gains only, while others represent net forest carbon stock changes that include plantations as well as deforestation carbon loses induced by bioenergy crops. On-going top-down land-use modelling developments should produce more refined characterization of forestry abatement alternatives and cost-effective mitigation potential in the near future. The results in Table 9.4 suggest a reasonable central estimate of about 700 million tonne CO2 in 2030 from forestry in competition with other sectors for achieving stabilization, significantly less than the regional bottom-up or global sector top-down estimates in this chapter summarized in Table 9.7.
Box 9.2: Commercial biomass for bioenergy from forests Current use of biomass from fuelwood and forest residues reaches 33 EJ (see Section 4.3.3). Three main categories of forest residues may be used for energy purposes: primary residues (available from additional stemwood fellings or as residues (branches) from thinning salvage after natural disturbances or final fellings); secondary residues (available from processing forest products) and tertiary residues (available after end use). Various studies have assessed the future potential supply of forest biomass (Yamamoto et al., 2001; Smeets and Faaij, 2007; Fischer and Schrattenholzer, 2001). Furthermore, some global biomass potential studies include forest residues aggregated with crop residue and waste (Sørensen, 1999). At a regional or national scale, studies are more detailed and often include economic considerations (Koopman, 2005; Bhattacharya et al., 2005; Lindner et al., 2005; Cuiping et al., 2004). Typical values of residue recoverability are between 25 and 50 % of the logging residues and between 33 and 80% of processing residues. Lower values are often assumed for developing regions (Yamamoto et al., 2001; Smeets and Faaij, 2007). At a global level, scenario studies on the future energy mixture (IPCC, 2000c; Sørensen, 1999; OECD, 2006) have included residues from the forestry sector in their energy supply (market potential). The technical potential of primary biomass sources given by the different global studies is aggregated by region in Table Box 9.2. From this table, it can conclude that biomass from forestry can contribute from about a few percent to about 15% (12 to 74 EJ/yr) of current primary energy consumption. It is outside the scope of this chapter to examine all pros and cons of increased production required for biomass for bioenergy (see Section 11.9).
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Box 9.2 continued Table 9.5. The technical potential of primary biomass for bioenergy from the forest sector at a regional level (in EJ/yr), for the period 2020-2050. The economic potential under 20 US$/tCO2 is assumed to be in the range of 10-20% of these numbers. Regions
EJ/yr LOW
HIGH
3 1 1
11 4 3
2
10
1 1 1 1 1
21 10 5 8 2
OECD OECD North America OECD Europe Japan + Australia + New Zealand Economies in Transition Central and Eastern Europe, the Caucasus and Central Asia Non-OECD Latin America Africa Non-Annex I East Asia Non-Annex I Other Asia Middle East World low and high estimates
12
74
World (based on global studies) assumed economic potential
14
65
Notes: Conversion factors used: 0.58 tonne dry matter/m3, a heating value of 15 GJ/tonne air dry matter, and a percentage of 49% carbon of dry matter. For example, 14 EJ (left column) is roughly comparable to 700 million tonnes of dry matter, which is (if assumed this has to come from additional stemwood fellings) comparable to roughly 1.5 billion m3 of roundwood, half of current global harvesting of wood. Sources: Fischer and Schrattenholzer, 2001; Ericsson and Nilsson, 2006; Yoshioka et al., 2006; Yamamoto, 2001; Williams, 1995; Walsh et al., 1999; Smeets and Faaij, 2007.
In general, the delivery or production costs of forestry residues are expected to be at a level of 1.0 to 7.7 US$/GJ. Smeets and Faaij (2007) concluded that at a global level, the economic potential of all types of biomass residues is 14 EJ/yr: at the very lower level of estimates in the table. This and the notion that the summation of the column of lower ranges of dry matter supply equals 700 million tonnes (which is assumed stemwood) is half of current global stemwood harvesting) was the reason to estimate the economic potential at 10-20% of above given numbers. The CO2 mitigation potential can only be calculated if the actual use and the amount of use of forestry biomass supply are known. This depends on the balance of supply and demand (see bioenergy in Section 11.3.1.4.). However, to give an indication of the order of magnitude of the figures the CO2-eq emissions avoided have been calculated from the numbers in Table 9.5 using the assumption that biomass replaces either coal (high range) or gas (low range). Based on these calculations8, the CO2-eq emissions avoided range from 420 to 4,400 MtCO2/yr for 2030. This is about 5 to 25% of the total CO2-eq emissions that originate from electricity production in 2030, as reported in the World Energy Outlook (OECD, 2006).
9.4.4
Global summation and comparison
An overview of estimates derived in the regional bottom-up estimates as given in Section 9.4.3.1 are presented in Table 9.6. Based on indications in literature and carbon supply curves, the fraction of the mitigation potential in the cost class < 20 US$/ tCO2 was estimated. Assuming a linear implementation rate of the measures, the values in Table 9.4 were adjusted to 2030 values (the values
8
required in the cross sector summation in Chapter 11, Table 11.3). The 2030 values are presented in Table 9.7 against the values derived from global forest sector models, and from global integrated models for three world regions. The mitigation effect of biomass for bioenergy (see text, Box 9.2) was excluded. The range of estimates in the literature and presented in Table 9.7 help in understanding the uncertainty surrounding forestry mitigation potential. Bottom-up estimates of mitigation generally include numerous activities in one or more regions
Assuming that it is used in a biomass combustion plant of 30% conversion efficiency and replaces a coal combustion plant with an efficiency of 48% (see IEA 2002) and a coal CO2 content of 95 kgCO2/GJ for the high range or a gas IGCC with an efficiency of 49% and a gas CO2 content of 57 kgCO2/GJ.
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Table 9.6: Summation of regional results (excluding bioenergy) as presented in Section 9.4.3.1 for 2040. Fraction by cost class is derived from Section 9.4.3.1. Economic potential in 2040 (MtCO2/yr) low
Economic potential in 2040 (MtCO2/yr) high
Fraction of total (technical) potential in cost class <20 US$/tCO2
400
820
0.2
90
180
0.2
Russian Federation
150
300
0.3
Africa
300
875
0.6
85
255
0.35
Caribbean, Central and South America
500
1750
0.6
Non Annex I East Asia
150
400
0.3
Non Annex I South Asia
300
875
0.6
1,975
5,455
North America Europe
OECD Pacific
Total
Note: These figures are surrounded by uncertainty. Differences in studies, assumptions, baselines, and price scenarios make a simple summation difficult.
Table 9.7: Comparison of estimates of economic mitigation potential by major world region and methodology excluding biomass for bioenergy in MtCO2/yr in 2030, at carbon prices less or equal to 100 US$/tCO2. Fraction by cost class is given in Tables 9.3 and 9.6. Regional bottom-up estimate Mean
Low
High
Global forest sector models
OECD
700
420
980
2,730
Economies in transition
150
90
210
3,600
Non-OECD Global
1,900
760
3,040
7,445
2,750a
1,270
4,230
13,775
Global integrated assessment models
700
a
Excluding bioenergy (see Box 9.2). Including the emission reduction effect of the economic potential of biomass for bioenergy would yield a total mean emission reduction potential (based on bottom up) of 3140 MtCO2/yr in 2030.
represented in detail. Top-down global modelling of sectors and of long-term climate stabilization scenario pathways generally includes fewer, simplified forest options, but allows competition across all sectors of the economy to generate a portfolio of least-cost mitigation strategies. Comparison of top-down and bottom-up modelling estimates (Figure 9.13) is difficult at present. This stems from differences in how the two approaches represent mitigation options and costs, market dynamics, and the effects of market prices on model and sectoral inputs and outputs such as labour, capital, and land. One important reason that bottom-up results yield a lower potential consistently for every region (Figure 9.13) is that this type of study takes into account (to some degree) barriers to implementation. The bottom-up estimate has, therefore, characteristics of a market potential study, but the degree is unknown.
carbon prices up to 100 US$/tCO2) to contribute between 1270 and 4230 MtCO2/yr in 2030 (medium confidence, medium agreement). About 50% of the medium estimate can be achieved at a cost under 20 US$/tCO2 (= 1550 MtCO2/yr: see Figure 9.14). The combined effects of reduced deforestation and degradation, afforestation, forest management, agro-forestry and bioenergy have the potential to increase gradually from the present to 2030 and beyond. For comparison with other sectors in Chapter 11, Table 11.2, data on cost categories <0 US$/tCO2 and 20-50 US$100/tCO2 have been derived from Tables 9.3 and 9.6, using cost information derived from regional bottom-up studies and global top- down modelling. The cost classes assessed should be seen as rough cost-class indications, as the information in the literature varies a lot. These analyses assume gradual implementation of mitigation activities starting at present.
The uncertainty and differences behind the studies referred to, and the lack of baselines are reasons to be rather conservative with the final estimate for the forestry mitigation potential. Therefore, mostly the bottom-up estimates are used in the final estimate. This stands apart from any preference for a certain type of study. Thus synthesizing the literature, we estimate that forestry mitigation options have the economic potential (at
This sink enhancement/emission avoidance will be located for 65% in the tropics (high confidence, high agreement; Figure 9.14); be found mainly in above-ground biomass; and for 10% achieved through bioenergy (medium confidence, medium agreement). In the short term, this potential is much smaller, with 1180 MtCO2/yr in 2010 (high confidence, medium agreement). Uncertainty from this estimate arises from the variety of studies
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3.500
Forestry
Mt CO2-eq
12000
Mt CO2/yr
top down
3.000
bottom up 2.500 2.000
10000 8000
1.500 6000
1.000 500
4000 2000
N
on
-A
C
nn
en
tra
la
nd Am So ex er u t h O I S ica EC ou D th N As or ia th Am er ic N a on -A Af nn ric ex a IE as tA si EI a T co un tri es Eu ro O pe EC D Pa ci fic M id dl e Ea st
0
Figure 9.13: Comparison of estimates of economic mitigation potential in the forestry sector (up to 100 US$/tCO2 in 2030) as based on global forest sector models (top-down) versus regional modelling results (bottom-up). Note: Excluding bioenergy; data from Table 9.3 and Table 9.6.
These final results allow comparison with earlier IPCC estimates for forestry mitigation potential (Figure 9.15). The estimates for Second Assessment Report (SAR), Third Assessment Report (TAR) and Special Report have to be seen as estimates for a technical potential, and are comparable to our Fourth Assessment Report (AR4) estimates for a carbon dioxide price < 100 US$/tCO2 (as displayed). As the bars in this figure are lined by the year to which they apply, one would expect an increasing trend towards the right-hand columns. This is not the
Mt CO2/y 20 - 100 US$/tonne CO2 < 20 US$/tonne CO2
800 600 400 200
pe ro Eu
O
EC
D
Pa
ci fi
c
A EE C C
As ia on Ea -An st ne As x I ia N
O th er
Af ric a
0 C an arib d be So a ut n, h Ce Am n e tra N or rica l th Am er ic a
2010 SR2030 AR4 2010 TAR 2050 TAR, 2030 AR4 LULUCF Forestry; Top- WG III, ch4, synthesis Forestry; Forestry and report. Forestry Regional down modelling Forestry agriculture modelling (< 20 US$tCO2) measures (< 20 US$tCO2)
Figure 9.15: Comparison of estimates of mitigation potential in previous IPCC reports (blue) and the current report (in red).
used, the different assumptions, the different measures taken into account, and not taking into account possible leakage between continents.
1000
0
Figure 9.14: Annual economic mitigation potential in the forestry sector by world region and cost class in 2030. Note: EECCA=Countries of Eastern Europe, the Caucasus and Central Asia.
Note the difference in years to which the estimate applies, in applied costs, and between forest sector only versus whole LULUCF estimates.
case. Instead a large variety is displayed. There is a trend visible through the consecutive IPCC reports, and not so much through the years to which the estimate applies. When ignoring the TAR synthesis, we start with the highest estimate in SAR (just over 8000 MtCO2/yr), then follows SR LULUCF with 5500 MtCO2, and TAR with 5300. Finally, the present report follows with a conservative estimate of 3140 (including bioenergy).
9.5 Interactions with adaptation and vulnerability Some of the mitigation potential as given in this chapter might be counteracted by adverse effects of climate change on forest ecosystems (Fischlin et al., 2007). Further, mitigation-driven actions in forestry could have positive adaptive consequences (e.g., erosion protection) or negative adaptation consequences (e.g., increase in pest and fires). Similarly, adaptation actions could have positive or negative consequences on mitigation. To avoid trade-offs, it is important to explore options to adapt to new climate circumstances at an early stage through anticipatory adaptation (Robledo et al., 2005). The limits to adaptation stem in part from the way that societies exacerbate rather than ameliorate vulnerability to climate fluctuations (Orlove, 2005) that can also affect mitigation potentials. There are significant opportunities for mitigation and for adapting to climate change, while enhancing the conservation of biodiversity, and achieving other environmental as well as socio-economic benefits. However, mitigation and adaptation have been considered separately in the global negotiations as well as in the literature 563
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until very recently. Now, the two concepts are seen to be linked, however to achieve synergies may be a challenge (Tol, 2006). In the IPCC Third Assessment Report, potential synergy and trade-off issues were not addressed. This section explores the synergy between mitigation and adaptation in the forest sector (Ravindranath and Sathaye, 2002). The potential and need for incorporating adaptation strategies and practices in mitigation projects is illustrated with a few examples. 9.5.1
Climate impacts on carbon sink and adaptation
In addition to natural factors, forest ecosystems have long been subjected to many human-induced pressures such as landuse change, over-harvesting, overgrazing by livestock, fire, and introduction of new species. Climate change constitutes an additional pressure that could change or endanger these ecosystems. The IPCC Fourth Assessment report (Fischlin et al., 2007 and Easterling et al., 2007) has highlighted the potential impacts of climate change on forest ecosystems. New findings indicate that negative climate change impacts may be stronger than previously projected and positive impacts are being overestimated as well as the uncertainty on predictions. Recent literature indicates that the projected potential positive effect of climate change as well as the estimated carbon sink in mature forests may be substantially threatened by enhancing or changing the regime of disturbances in forests such as fire, pests, drought, and heat waves, affecting forestry production including timber (Fuhrer et al., 2007; Sohngen et al., 2005; Ciais et al., 2005). Most model limitations persist; models do not include key ecological processes, and feedbacks. There are still inconsistencies between the models used by ecologists to estimate the effects of climate change on forest production and composition, and the models used by foresters to predict forest yield (Easterling et al., 2007). Despite the achievements and individual strengths of the selected modelling approaches, core problems of global land-use modelling have not yet been resolved. For a new generation of integrated large-scale land-use models, a transparent structure would be desirable (Heistermann et al., 2006). Global change, including the impacts of climate change, can affect the mitigation potential of the forestry sector by either increasing (nitrogen deposition and CO2 fertilization), or decreasing (negative impacts of air pollution,) the carbon sequestration. But, recent studies suggest that the beneficial impacts of climate change are being overestimated by ignoring some of the feedbacks (Körner, 2004) and assumption of linear responses. Also, the negative impacts may be larger than expected (Schroter et al., 2005), with either some effects remaining incompletely understood (Betts et al., 2004) or impossible to separate one from the other.
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9.5.2
Mitigation and adaptation synergies
The mitigation and adaptation trade-offs and synergies in the forestry sector are dealt with in Klein et al. (2007). Many of the response strategies to address climate change, such as Global Environmental Facility (GEF) and Clean Development Mechanism (CDM), Activities under Article 3.3 and Article 3.4 and the Adaptation Fund aim at implementation of either mitigation or adaptation technologies or policies. It is necessary to promote synergy in planning and implementation of forestry mitigation and adaptation projects to derive maximum benefit to the global environment as well as local communities or economies, for example promoting adaptive forest management (McGinley & Finegan, 2003). However, recent analyses not specifically focused on the Forestry sector point out that it may be difficult to enhance synergies. This is due to the different actors involved in mitigation and adaptation, competitive use of funds, and the fact that in many cases both activities take place at different implementation levels (Tol, 2006). It should also be taken into account that activities to address mitigation and adaptation in the forestry sector are planned and implemented locally. It is likely that adaptation practices will be easier to implement in forest plantations than in natural forests. Several adaptation strategies or practices can be used in the forest sector, including changes in land use choice (Kabat et al., 2005), management intensity, hardwood/softwood species mix, timber growth and harvesting patterns within and between regions, changes in rotation periods, salvaging dead timber, shifting to species more productive under the new climatic conditions, landscape planning to minimize fire and insect damage, and to provide connectivity, and adjusting to altered wood size and quality (Spittlehouse and Stewart, 2003). A primary aim of adaptive management is to reduce as many ancillary stresses on the forest resource as possible. Maintaining widely dispersed and viable populations of individual species minimizes the probability that localized catastrophic events will cause extinction (Fischlin et al., 2007). While regrowth of trees due to effective protection will lead to carbon sequestration, adaptive management of protected areas also leads to conservation of biodiversity and reduced vulnerability to climate change. For example, ecological corridors create opportunities for migration of flora and fauna, which facilitates adaptation to changing climate. Adaptation practices could be incorporated synergistically in most mitigation projects in the forest sector. However, in some cases, mitigation strategies could also have adverse implications for watersheds in arid and semi-arid regions (UK FRP, 2005) and biodiversity (Caparros and Jacquemont, 2003). To achieve an optimum link between adaptation and mitigation activities, it is necessary to clearly define who does the activity, where and what are the activities for each case. Several principles can be defined (Murdiyarso et al., 2005): prioritizing mitigation activities that help to reduce pressure on natural resources, including vulnerability to climate change as
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Forestry
Table 9.8: Adaptation and mitigation matrix Mitigation option
Vulnerability of the mitigation option to climate change
Adaptation options
Implications for GHG emissions due to adaptation
A. Increasing or maintaining the forest area Reducing deforestation and forest degradation
Vulnerable to changes in rainfall, higher temperatures (native forest dieback, pest attack, fire and, droughts)
Fire and pest management Protected area management Linking corridors of protected areas
No or marginal implications for GHG emissions, positive if the effect of perturbations induced by climate change can be reduced
Afforestation / Reforestation
Vulnerable to changes in rainfall, and higher temperatures (increase of forest fires, pests, dieback due to drought)
Species mix at different scales Fire and pest management Increase biodiversity in plantations by multi-species plantations. Introduction of irrigation and fertilisation Soil conservation
No or marginal implications for GHG emissions, positive if the effect of perturbations induced by climate change can be reduced May lead to increase in emissions from soils or use of machinery and fertilizer
B. Changing forest management: increasing carbon density at plot and landscape level Forest management in plantations
Vulnerable to changes in rainfall, and higher temperatures (i.e. managed forest dieback due to pest or droughts)
Pest and forest fire management. Adjust rotation periods Species mix at different scales
Marginal implications on GHGs. May lead to increase in emissions from soils or use of machinery or fertilizer use
Forest management in native forest
Vulnerable to changes in rainfall, and higher temperatures (i.e. managed forest dieback due to pest, or droughts)
Pest and fire management Species mix at different scales
No or marginal
C. Substitution of energy intensive materials Increasing substitution of fossil energy intensive products by wood products
Stocks in products not vulnerable to climate change
No implications in GHGs emissions
An intensively managed plantation Suitable selection of species to from where biomass feedstock cope with changing climate comes is vulnerable to pests, Pest and fire management drought and fire occurrence, but the activity of substitution is not.
No implications for GHG emissions except from fertilizer or machinery use
D. Bioenergy Bioenergy production from forestry
a risk to be analysed in mitigation activities; and prioritizing mitigation activities that enhance local adaptive capacity, and promoting sustainable livelihoods of local populations. Considering adaptation to climate change during the planning and implementation of CDM projects in forestry may also reduce risks, although the cost of monitoring performance may become very complex (Murdiyarso et al., 2005). Adaptation and mitigation linkages and vulnerability of mitigation options to climate change are summarized in Table 9.8, which presents four types of mitigation actions. Reducing deforestation is the dominant mitigation option for tropical regions (Section 9.4). Adaptive practices may be complex. Forest conservation is a critical strategy to promote sustainable development due to its importance for biodiversity conservation, watershed protection and promotion of livelihoods
of forest-dependent communities in existing natural forest (IPCC, 2002). Afforestation and reforestation are the dominant mitigation options in specific regions (e.g., Europe). Currently, afforestation and reforestation are included under Article 3.3 and in Articles 6 and 12 (CDM) of the Kyoto Protocol. Plantations consisting of multiple species may be an attractive adaptation option as they are more resilient, or less vulnerable, to climate change. The latter as a result of different tolerance to climate change characteristic of each plantation species, different migration abilities, and differential effectiveness of invading species (IPCC, 2002). Agro-forestry provides an example of a set of innovative practices designed to enhance overall productivity, to increase carbon sequestration, and that can also strengthen the system’s 565
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ability to cope with adverse impacts of changing climate conditions. Agro-forestry management systems offer important opportunities creating synergies between actions undertaken for mitigation and for adaptation (Verchot et al., 2006). The area suitable for agro-forestry is estimated to be 585-1215 Mha with a technical mitigation potential of 1.1 to 2.2 PgC in terrestrial ecosystems over the next 50 years (Albrecht and Kandji, 2003). Agro-forestry can also help to decrease pressure on natural forests and promote soil conservation, and provide ecological services to livestock. Bioenergy. Bioenergy plantations are likely to be intensively managed to produce the maximum biomass per unit area. To ensure sustainable supply of biomass feedstock and to reduce vulnerability to climate change, the practices mentioned above for afforestation and reforestation projects need to be explored such as changes in rotation periods, salvage of dead timber, shift to species more productive under the new climatic conditions, mixed species forestry, mosaics of different species and ages, and fire protection measures. Adaptation and development
mitigation
synergy
and
sustainable
The need for integration of mitigation and adaptation strategies to promote sustainable development is presented in Klein et al. (2007). The analysis has shown the complementarity or synergy between many of the adaptation options and mitigation (Dang et al., 2003). Promotion of synergy between mitigation and adaptation will also advance sustainable development, since mitigation activities could contribute to reducing the vulnerability of natural ecosystems and socioeconomic systems (Ravindranath, 2007). Currently, there are very few ongoing studies on the interaction between mitigation, adaptation and sustainable development (Wilbanks, 2003; Dang et al., 2003). Quantification of synergy is necessary to convince the investors or policy makers (Dang et al., 2003). The possibility of incorporating adaptation practices into mitigation projects to reduce vulnerability needs to be explored. Particularly, Kyoto Protocol activities under Article 3.3, 3.4 and 12 provide an opportunity to incorporate adaptation practices. Thus, guidelines may be necessary for promoting synergy in mitigation as well as adaptation programmes and projects of the existing UNFCCC and Kyoto Protocol mechanisms as well as emerging mechanisms. Integrating adaptation practices in such mitigation projects would maximize the utility of the investment flow and contribute to enhancing the institutional capacity to cope with risks associated with climate change (Dang et. al., 2003).
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9.6 Effectiveness of and experience with policies This section examines the barriers, opportunities, and implementation issues associated with policies affecting mitigation in the forestry sector. Non-climate policies, that is forest sector policies that affect net greenhouse gas emissions from forests, but that are not designed primarily to achieve climate objectives, as well as policies primarily designed to reduce net forest emissions are considered. Many factors influence the efficacy of forest policies in achieving intended impacts on forest land-use, including land tenure, institutional and regulatory capacity of governments, the financial competitiveness of forestry as a land use, and a society’s cultural relationship to forests. Some of these factors typically differ between industrialized and developing countries. For example, in comparison to developing countries, industrialized countries tend to have relatively small amounts of unallocated public lands, and relatively strong institutional and regulatory capacities. Where appropriate, policy options and their effectiveness are examined separately for industrialized and developing countries. Because integrated and non-climate policies are designed primarily to achieve objectives other than net emissions reductions, evaluations of their effectiveness focus primarily on indicators, such as maintenance of forest cover. This provides only partial insight into their potential to mitigate climate change. Under conditions with high potential for leakage, for example, such indicators may overestimate the potential for carbon benefits (Section 9.6.3). 9.6.1
Policies aimed at reducing deforestation
Deforestation in developing countries, the largest source of emissions from the forestry sector, has remained at high levels since 1990 (FAO, 2005). The causes of tropical deforestation are complex, varying across countries and over time in response to different social, cultural, and macroeconomic conditions (Geist and Lambin, 2002). Broadly, three major barriers to enacting effective policies to reduce forest loss are: (i) profitability incentives often run counter to forest conservation and sustainable forest management (Tacconi et al., 2003); (ii) many direct and indirect drivers of deforestation lie outside of the forest sector, especially in agricultural policies and markets (Wunder, 2004); and (iii) limited regulatory and institutional capacity and insufficient resources constrain the ability of many governments to implement forest and related sectoral policies on the ground (Tacconi et al., 2003). In the face of these challenges, national forest policies designed to slow deforestation on public lands in developing countries have had mixed success: • In countries where institutional and regulatory capacities are insufficient, new clearing by commercial and small-scale agriculturalists responding to market signals continues to be a dominant driver of deforestation (Wunder, 2004).
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• A number of national initiatives are underway to combat illegal logging (Sizer et al., 2005). While these have increased the number of charges and convictions, it is too early to assess their impact on forest degradation and deforestation. • Legally protecting forests by designating protected areas, indigenous reserves, non-timber forest reserves and community reserves have proven effective in maintaining forest cover in some countries, while in others, a lack of resources and personnel result in the conversion of legally protected forests to other land uses (Mertens et al., 2004). China (Cohen et al., 2002), the Philippines and Thailand (Granger, 1997) have significantly reduced deforestation rates in response to experiencing severe environmental and public health consequences of forest loss and degradation. In India, the Joint Forest Management programme has been effective in partnering with communities to reduce forest degradation (Bhat et al., 2001). These examples indicate that strong and motivated government institutions and public support are key factors in implementing effective forest policies. Options for maintaining forests on private lands in developing countries are generally more limited than on public lands, as governments typically have less regulatory control. An important exception is private landholdings in the Brazilian Amazon, where the government requires that landowners maintain 80% of the property under forest cover. Although this regulation has had limited effectiveness in the past (Alves et al., 1999), recent experience with a licensing and monitoring system in the state of Mato Grosso has shown that commitment to enforcement can significantly reduce deforestation rates. A recently developed approach is for governments to provide environmental service payments to private forest owners in developing countries, thereby providing a direct financial incentive for the retention of forest cover. Relatively high transaction costs and insecure land and resource tenure have thus far limited applications of this approach in many countries (Grieg-Gran, 2004). However, significant potential may exist for developing payment schemes for restoration and retention of forest cover to provide climate mitigation (see below) and watershed protection services. In addition to national-level policies, numerous international policy initiatives to support countries in their efforts to reduce deforestation have also been attempted: • Forest policy processes, such as the UN Forum on Forests, and the International Tropical Timber Organization have provided support to national forest planning efforts but have not yet had demonstrable impacts on reducing deforestation (Speth, 2002). • The World Bank has modified lending policies to reduce the risk of direct negative impacts to forests, but this does not appear to have measurably slowed deforestation (WBOED, 2000).
Forestry
• The World Bank and G-8 have recently initiated the Forest Law Enforcement and Governance (FLEG) process among producer and consumer nations to combat illegal logging in Asia and Africa (World Bank, 2005). It is too early to assess the effectiveness of these initiatives on conserving forests stocks. • The Food and Agricultural Organization (FAO) Forestry Programme has for decades provided a broad range of technical support in sustainable forest management (FAO, 2006b); assessing measurable impacts has been limited by the lack of an effective monitoring programme (Dublin and Volante, 2004). Taken together, non-climate policies have had minimal impact on slowing tropical deforestation, the single largest contribution of land-use change to global carbon emissions. Nevertheless, there are promising examples where countries with adequate resources and political will have been able to slow deforestation. This raises the possibility that, with sufficient institutional capacity, financial incentives, political will and sustained financial resources, it may possible to scale up these efforts. One potential source of additional financing for reducing deforestation in developing countries is through wellconstructed carbon markets or other environmental service payment schemes (Winrock International, 2004; Stern, 2006). Under the UNFCCC and Kyoto Protocol, no climate policies currently exist to reduce emissions from deforestation or forest degradation in developing countries. The decision to exclude avoided deforestation projects from the CDM in the Kyoto Protocol’s first commitment period was in part based on methodological concerns. These concerns are particularly associated with additionality and baseline setting and whether leakage could be sufficiently controlled or quantified to allow for robust carbon crediting (Trines et al., 2006). In December 2005, COP-11 established a two-year process to review relevant scientific, technical, and methodological issues and to consider possible policy approaches and positive incentives for reducing emissions from deforestation in developing countries (UNFCCC, 2006). Recent studies suggests a broad range of possible architectures by which future climate policies might be designed to effectively reduce emissions from tropical deforestation and forest degradation (Schlamadinger et al., 2005; Trines et al., 2006). For example, Santilli et al. (2005), propose that non-Annex I countries might, on a voluntary basis, elect to reduce their national emissions from deforestation. The emission reductions could then be credited and sold to governments or international carbon investors at the end of a commitment period, contingent upon agreement to stabilize, or further reduce deforestation rates in the subsequent commitment periods. One advantage of a national-sectoral approach over a projectbased approach to reduce emissions from deforestation relates to leakage, in that any losses in one area could be balanced 567
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against gains in other areas. This does not entirely address the leakage problem since the risk of international leakage remains, as occurs in other sectors. Other proposals emphasize accommodation to diverse national circumstances, including differing levels of development, and include a suggestion of separate targets for separate sectors (Grassl et al., 2003). This includes a “no-lose” target, whereby emission allowances can be sold if the target is reached. No additional emission allowances would have to be bought if the target was not met. A multi-stage approach such that the level of commitment of an individual country increases gradually over time; capacity building and technology research and development; or quantified sectoral emission limitation and reduction commitments similar to Annex 1 commitments under the Kyoto Protocol (Trines et al., 2006).
can reforest these lands directly. In cases where such capacities are more limited, governments may enter into joint management agreements with communities, so that both parties share the costs and benefits of plantation establishment (Williams, 2002). Incentives for plantation establishment may take the form of afforestation grants, investment in transportation and roads, energy subsidies, tax exemptions for forestry investments, and tariffs against competing imports (Cossalter and PyeSmith, 2003). In contrast to conservation of existing forests, the underlying financial incentives to establish plantations may be positive. However, the creation of virtually all significant plantation estates has relied upon government support, at least in the initial stages. This is due, in part, to the illiquidity of the investment, the high cost of capital establishment and long waiting period for financial return. 9.6.3
Proposed financing mechanisms include both carbon market-based instruments (Stern, 2006) and non-market based channels, for example, through a dedicated fund to voluntarily reduce emissions from deforestation (UNFCCC, 2006). Box 9.3 discusses recent technical advances relevant to the effective design and implementation of climate policies aimed at reducing emissions from deforestation and forest degradation.
9.6.2
Policies aimed to promote afforestation and reforestation
Non-climate forest policies have a long history in successful creation of plantation forests on both public and private lands in developing and developed countries. If governments have strong regulatory and institutional capacities, they may successfully control land use on public lands, and state agencies
Policies to improve forest management
Industrialized countries generally have sufficient resources to implement policy changes in public forests. However, the fact that these forests are already managed to relatively high standards may limit possibilities for increasing sequestration through changed management practices (e.g., by changing species mix, lengthening rotations, reducing harvest damage and or accelerating replanting rates). There may be possibilities to reduce harvest rates to increase carbon storage however, for example, by reducing harvest rates and/or harvest damage. Governments typically have less authority to regulate land use on private lands, and so have relied upon providing incentives to maintain forest cover, or to improve management. These incentives can take the form of tax credits, subsidies, cost sharing, contracts, technical assistance, and environmental service payments. In the United States, for example, several
BOX 9.3: Estimating and monitoring carbon emissions from deforestation and degradation Recent analyses (DeFries et al., 2006; UNFCCC, 2006) indicate considerable progress since the Third Assessment Report and the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (IPCC, 2003) in data acquisition and development of methods and tools for estimating and monitoring carbon emissions from deforestation and forest degradation in developing countries. Remote sensing approaches to monitoring changes in land cover/land use at multiple scales and coverage are now close to operational on a routine basis. Measuring forest degradation through remote sensing is technically more challenging, but methods are being developed (DeFries et al., 2006). Various methods can be applied, depending on national capabilities, deforestation patterns, and forest characteristics. Standard protocols need to be developed for using remote sensing data, tools and methods that suit both the variety of national circumstances and meet acceptable levels of accuracy. However, quantifying accuracy and ensuring consistent methods over time are more important than establishing consistent methods across countries. Several developing countries, including India and Brazil, have systems in place for national-scale monitoring of deforestation (DeFries et al., 2006). While well-established methods and tools are available for estimating forest carbon stocks, dedicated investment would be required to expand carbon stock inventories so that reliable carbon estimates can be applied to areas identified as deforested or degraded through remote sensing. With sound data on both change in forest cover and on change in carbon stocks resulting from deforestation and degradation, emissions can be estimated using methods described by the new IPCC Inventory Guidelines (IPCC, 2006).
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government programmes promote the establishment, retention, and improved management of forest cover on private lands, often of marginal agricultural quality (Box 9.4; Gaddis et al., 1995). The lack of robust institutional and regulatory frameworks, trained personnel, and secure land tenure has constrained the effectiveness of forest management in many developing countries (Tacconi et al., 2003; Box 9.5). Africa, for example, had about 649 million forested hectares as of 2000 (FAO, 2001). Of this, only 5.5 million ha (0.8%) had long-term management plans, and only 0.9 million ha (0.1%) were certified to sound forestry standards. Thus far, efforts to improve logging practices in developing countries have met with limited success. For example, reduced-impact logging (RIL) techniques would increase carbon storage over traditional logging, but have not been widely adopted by logging companies, even when they lead to cost savings (Holmes et al., 2002). Nevertheless, there are several examples where large investments in building technical and institutional capacity have dramatically improved forestry practices (Dourojeanni, 1999). Policies aimed at liberalizing trade in forest products have mixed impacts on forest management practices. Trade liberalization in forest products can enhance competition and can make improved forest management practices more economically attractive in mature markets (Clarke, 2000). But, in the relatively immature markets of many developing countries, liberalization may act to magnify the effects of policy and market failures (Sizer et al., 1999). The recent FAO forest assessment conservatively estimates that insects, disease and fire annually impact 3.2% of the forests in reporting countries (FAO, 2005). Policies that successfully increase the forest protection against natural disturbance agents may reduce net emissions from forest lands (Richards et al., 2006). In industrialized countries, a history of fire suppression and a lack of thinning treatments have created high fuel loads in many public forests, such that when fires do occur, they release large quantities of carbon (Schelhaas et al., 2003). A major technical obstacle is designing careful management interventions to reduce fuel loading and to restore landscape heterogeneity to forest structure (USDA Forest Service, 2000). Scaling up their application to large forested areas, such as in Western USA, Northern Canada or Russia, could lead to large gains in the conservation of existing carbon stocks (Sizer et al., 2005). Forest fire prevention and suppression capacities are rudimentary in many developing countries, but trial projects show that with sufficient resources and training, significant reductions in forest fires can be achieved (ITTO, 1999). Voluntary certification to sustainable forest management standards aims to improve forest management by providing incentives such as increased market access or price premiums to certified producers who meet these standards. Various
Forestry
certification schemes have collectively certified hundreds of millions of hectares in the last decade and certification can result in measurable improvements in management practices (Gullison, 2003). However, voluntary certification efforts to date continue to be challenged in improving the management of forest managers operating at low standards, where the potential for improvement and net emissions reductions are greatest. One possible approach to overcome current barriers in areas with weak forest management practices is to include stepwise or phased approaches to certification (Atyi and Simula, 2002). 9.6.4
Policies to increase substitution of forestderived biofuels for fossil fuels and biomass for energy-intensive materials
Countries may promote the use of bioenergy for many non-climate reasons, including increasing energy security and promoting rural development (Parris, 2004). Brazil, for example, has a long history of encouraging plantation establishment for the production of industrial charcoal by offering a combination of tax exemption for plantation lands, tax exemption for income originating from plantation companies, and deductibility of funds used to establish plantations (Couto and Betters, 1995). The United States provides a range of incentives for ethanol production including exclusion from excise taxes, mandating clean air performance requirements that created markets for ethanol, and tax incentives and accelerated depreciation schedules for electricity generating equipment that burn biomass (USDOE, 2005). The Australian Government’s Mandatory Renewable Energy Target, which seeks to create a market for renewable energy, provides incentives for the development of renewable energy from plantations and wood waste (Government of Australia, 2006). Building codes and other government policies that, where appropriate, can promote substitution of use of sustainably harvested forest products wood for more energy-intensive construction materials may have substantial potential to reduce net emissions (Murphy, 2004). Private companies and individuals may also modify procurement to prefer or require certified wood from well-managed forests on environmental grounds. Such efforts might be expanded once the climate mitigation benefits of sustainably harvested wood products are more fully recognized. 9.6.5
Strengthening the role of forest policies in mitigating climate change
Policies have generally been most successful in changing forestry activities where they are consistent with underlying profitability incentives, or where there is sufficient political will, financial resources and regulatory capacity for effective implementation. Available evidence suggests that policies that seek to alter forestry activities where these conditions do not apply have had limited effectiveness. Additional factors that influence the potential for non-climate policies to reduce net 569
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Box 9.4: Non-climate forest policies as an element of carbon management in the United States Many programmes in the United States support the establishment, retention, and improved management of forest cover on private lands. These entail contracts and subsidies to private landowners to improve or change land-use management practices. USDA also provides technical information, research services, cost sharing and other financial incentives to improve land management practices, including foresting marginal agricultural lands, and improving the management of existing of forests. Examples include the Conservation Reserve Program; Forestry Incentives Program, and Partners for Wildlife; (Richards et al., 2006). For example, in the 20-year period between 1974 and 1994, the Forestry Incentives Program spent 200 US$ million to fund 1.34 million hectares of tree planting; 0.58 million hectares of stand improvement; and 11 million hectares of site preparation for natural regeneration (Gaddis et al., 1995). Richards et al. (2006) suggest that substantial gains in carbon sequestration and storage could be achieved by increasing the resources and scope of these programmes and through new results-based programmes, which would reward landowners based on the actual carbon they sequester or store.
Box 9.5: Non-climate forest policies as an element of carbon management in Africa Forest and land use policies across African countries have historically passed through two types of governance: Under traditional systems controlled by families, traditional leaders and communities, decisions regarding land allocation, redistribution and protection were the responsibility of local leaders. Most land and resources were under relatively sustainable management by nomadic or agro-pastoralist communities who developed systems to cope with vulnerable conditions. Agriculture was typically limited to shifting cultivation, with forest and range resources managed for multiple benefits. Under central government systems, land-use policies are sectoral-focused, with strong governance in the agricultural sector. Agriculture expansion policies typically dominate land use at the expense of forestry and rangeland management. This has greatly influenced present day forest and range policies and practices and resulted in vast land degradation (IUCN, 2002; 2004).The adoption of centralized land management policies and legislation system has often brought previously community-oriented land management systems into national frameworks, largely without the consent and involvement of local communities. Central control is reflected in large protected areas, with entry of local communities prevented. Presently, contradiction and conflicts in land-use practices between sectors and communities is common. Negotiations demanding decentralization and equity in resource distribution may lead to changes in land tenure systems in which communities and official organizations will increasingly agree to collaboration and joint management in which civil societies participate. Parastatal institutions, established in some countries, formulate and implement policies and legislation that coordinate between sectors and to encourage community participation in land and resource management. Land tenure categories characteristically include private holdings (5–25% of national area), communal land (usually small percentage) and state lands (the majority of the land under government control). Each faces many problems generated by conflicting rights of use and legislation that gives greater government control on types of resource use even under conditions of private ownership. Land control system and land allocation policy adopted by central governments often have negative impacts on land and tree tenure. Local communities are not encouraged to plant, conserve and manage trees on government owned land that farmers use on lease systems. Even large-scale farmers who are allocated large areas for cultivation, abandon the land and leave it as bare when it becomes non-productive. Forest lands reserved and registered under community ownership are communally managed on the basis of stakeholder system and shared benefits. Evidence from many case studies in Sudan suggests that integrated forest management where communities have access rights to forest lands and are involved in management, is a key factor favouring the restoration of forest carbon stocks (IUCN, 2004). These projects provide examples of a collaborative system for the rehabilitation and use of the forest land property based on defined and acceptable criteria for land cultivation by the local people and for renewal of the forest crop.
emissions from the forest sector include their ability to (1) provide relatively large net reductions per unit area; (2) be potentially applicable at a large geographic scale; and, (3) have relatively low leakage (Niesten et al., 2002).
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By these criteria, promising approaches across both industrialized and developing countries include policies that combat the loss of public forests to natural disturbance agents, and “Payment for Environmental Services” (PES) systems that provide an incentive for the retention of forest cover. In
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both cases, there are good examples where they have been successfully implemented at small scales, and the impediments to increasing scale are relatively well understood. There is also a successful history of policies to create new forests, and these have led to large on-site reductions in net emissions. Care must be taken, however, to make sure that at plantation creation, there is no displacement of economic or subsistence activities that will lead to forest clearing elsewhere. Policies to increase the substitution of fossil fuels with bioenergy have also had a large positive impact on net emissions. If feedstock is forestry waste, then there is little potential leakage. If new plantations are created for biofuel, then care must be taken to reduce leakage. Because forestry policies tend not to have climate mitigation as core objective, leakage and other factors that may limit net reductions are generally not considered. This may change as countries begin to integrate climate change mitigation objectives more fully into national forestry policies. Countries where such integration is taking place include Costa Rica, the Dominican Republic, and Peru (Rosenbaum et al., 2004). 9.6.6
Lessons learned from project-based afforestation and reforestation since 2000
Experience is limited by the fact that Joint Implementation is not operational yet, and the first call for afforestation and reforestation (A/R) methodologies under CDM was only issued in September 2004. In addition, the modalities and procedures for CDM A/R as decided in December 2003 are complex. Nevertheless, the capacities built up through the development of projects and related methodologies should not be underestimated. As of November 2006, 27 methodologies were submitted, 17 from Latin America, four from Asia and Africa respectively, and two from Eastern Europe. The four which were approved by the CDM Executive Board relate to projects located in China, Moldova, Albania and Honduras and all consist of planting forests on degraded agricultural land. In anticipation of Joint Implementation, several projects are under development in several Annex I countries in Eastern Europe, notably in Romania, Ukraine and the Czech Republic.
use activities reflected in the baseline. Populations previously active on the project area may shift their activities to other areas. In land protection projects, logging companies may shift operations or buy timber from outside the project area to compensate for reduced supply of the commodity (activity outsourcing). Secondary leakage is not linked to project participants or previous actors on the area. It is often a market effect, where a project increases (by forest plantation) or decreases (deforestation avoidance) wood supply. Quantitative estimates of leakage (Table 9.9) suggest that leakage varies by mitigation activity and region. The order of magnitude and even the direction of leakage (negative versus positive), however, depend on the project design (Schwarze et al., 2003). Leakage risk is likely to be low if a whole country or sector is involved in the mitigation activity, or if project activities are for subsistence and do not affect timber or other product markets. There are also welldocumented methods to minimize leakage of project-based activities. For example, afforestation projects can be combined with biomass energy plants, or they may promote the use of timber as construction material. Fostering agricultural intensification in parallel can minimize negative leakage from increased local land demand. Where a project reduces deforestation, it can also reduce pressure on forest lands, for example, by intensifying the availability of fuel wood from other sources for local communities. Projects can be designed to engage local people formerly responsible for deforestation in alternative income-generating activities (Sohngen and Brown, 2004). Leakage appears to have a time dimension as well, due to the dynamics of the forest carbon cycle and management (for example, timing of harvest, planting and regrowth, or protection). Analysis in the USA indicates that national afforestation in response to a carbon price of 15 US$/tCO2 would have 39% leakage in the first two decades, but decline to 24% leakage over five to ten decades, due to forest management dynamics (US EPA, 2005). 9.6.6.2
There are voluntary project-based activities in the USA, with a programme for trading certificates established by the Chicago Climate Exchange (Robins, 2005). The Voluntary Reporting (1605 (b)) Program of the US Department of Energy (USDOE, 2005) provides reporting guidelines for forestry activities. Since the Special Report on LULUCF (IPCC, 2000a), there has been methodological progress in several areas discussed below. 9.6.6.1
Leakage
There is no indication that leakage effects are necessarily higher in forestry than in project activities in other sectors but they can be significant (Chomitz, 2002). Some studies distinguish between primary and secondary effects. A primary effect is defined as resulting from agents that perform land
Potential non-permanence of carbon storage
The reversibility of carbon removal from the atmosphere creates liability issues whenever integrating land use in any kind of accounting system. There needs to be a liability for the case that carbon is released back into the atmosphere because Parties to the UNFCCC agreed, “…that reversal of any removal due to land use, land-use change and forestry activities be accounted for at the appropriate point in time” (UNFCCC, 2001). In 2000, the Colombian delegation first presented a proposal to create expiring Certified Emission Reductions under CDM (UNFCCC, 2001). Its basic idea is that the validity of Certified Emission Reductions (CERs) from afforestation and reforestation project activities under CDM is linked to the time of existence of the relating stocks. The principle of temporary crediting gained support over the subsequent years. 571
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Table 9.9: Forestry mitigation activity leakage estimates by activity, estimation method and region from the literature Activity
Region
Leakage estimation method
Afforestation of degraded lands
Kolar district, Karnataka, India hypothetical project
Estimated leakage rate (% of carbon mitigation)
Source
Afforestation: tropical region estimates Household wood demand survey
0.02
Ravindranath, et al., 2007
19 – 41
Authors estimates based on Lasco et al., 2007
Plantations, forest Magat watershed, conservation, agro-forestry Philippines hypothetical of degraded lands project
Historical rates of technology adoption
Afforestation on small landowner parcels
Scolel Té project, Chiapas, Mexico
Household wood demand survey
0 (some positive leakage)
De Jong et al., 2007
Afforestation degraded uplands
Betalghat hypothetical project, Uttaranchal, India
Household wood demand survey
10 from fuelwood, fodder
Hooda et al., 2007
Afforestation, farm forestry
Bazpur hypothetical project, Uttaranchal, India
Household wood demand survey
20 from fuelwood, poles
Hooda et al., 2007
Afforestation: global and temperate region estimates Afforestation (plantation establishment)
Global
PEM
0.4-15.6
Afforestation
USA-wide
PEM
18-42
Afforestation only
USA-wide
PEM
24
Afforestation and forest management jointly
USA-wide
PEM
-2.8
Sedjo and Sohngen, 2000 Murray et al., 2004 US EPA, 2005
a)
US EPA, 2005
Avoided deforestation: tropical region estimates Avoided deforestation
Bolivia, Noel Kempff project and national
PEM
2-38 discounted 5-42 undiscounted
Sohngen and Brown, 2004
Avoided deforestation and biofuels: temperate region estimates
a)
Avoided deforestation
Northeast USA
PEM
41-43
Avoided deforestation
Rest of USA
PEM
0-92
US EPA, 2005
Avoided deforestation
Pacific Northwest USA
PEM
8-16
US EPA, 2005
Avoided deforestation (reduced timber sales)
Pacific Northwest USA
Econometric model
Biofuel production (short rotation woody crops)
USA
PEM
43 West region 58 Continental US 84 US and Canada 0.2
US EPA, 2005
Wear and Murray, 2004
US EPA, 2005
Negative leakage rate means positive leakage; PEM means partial equilibrium model of forest and/or agriculture sector(s).
Source: Sathaye and Andrasko, 2007
Consequently, the Milan Decision 19/CP.9 (UNFCCC, 2003) created two types of expiring CERs: temporary CERs - tCERs and long-term CERs - lCERs. The validity of both credit types is limited and reflected on the actual certificate. The credit owner is liable to replace them when they expire or when the relating stocks are found to be lost at the end of the commitment period. Afforestation and reforestation projects need to be verified first at a time at the discretion of the project participants, and in intervals of exactly five years thereafter. The value of temporary CERs critically depends on the market participants’ mitigation cost expectations for future commitment periods. Assuming constant carbon prices, the price for a temporary CER during the first commitment period is estimated to range between 14 and 35 % of that of a permanent CER from any other mitigation 572
activity (Dutschke, et al., 2005). This solution is safe from the environmental integrity point of view, yet it has created much uncertainty among project developers (Pedroni, 2005). 9.6.6.3
Additionality and baselines
A project that claims carbon credits for mitigation needs to demonstrate its additionality by proving that the same mitigation effect would not have taken place without the project. For CDM, the Executive Board’s Consolidated Additionality Tool offers a standardized procedure to project developers. Specific for CDM afforestation and reforestation (A/R), there is an area eligibility test along the forest definitions provided under the relevant Decision 11/CP.7 in order to avoid implementation
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on areas that prior to the project start were forests in 1990 or after. In the modalities and procedures for CDM, there are three different baseline approaches available for A/R. So far, only one has been successfully applied in the four approved methodologies. 9.6.6.4
to overcome uncertainty among potential buyers and investors, and to prevent negative social and environmental impacts.
9.7 Forests and Sustainable Development
Monitoring
For project monitoring, there is now an extended guidance available (IPCC, 2006; USDOE, 2005). Monitoring costs depend on many variables, including the project complexity (including the number of stakeholders involved), heterogeneity of the forest type, the number and type of carbon pools, and GHG to be monitored and the appropriate measurement frequencies. There is a trade-off between the completeness of monitoring data and the carbon price that can be achieved: monitoring costs can sum up an important share of a project’s transaction costs. Proper design of the monitoring plan is, therefore, essential for the economic viability of forestry projects. If project developers can demonstrate that omitting particular carbon pools from the project’s quantification exercise does not constitute an overestimate of the project’s GHG benefits, such pools may be left outside the monitoring plan.
Sustainable forest management of both natural and planted forests is essential to achieving sustainable development. It is a means to reduce poverty, reduce deforestation, halt the loss of forest biodiversity, and reduce land and resource degradation, and contribute to climate change mitigation. Forests play an important role in stabilization of greenhouse gas concentrations in the atmosphere while promoting sustainable development (Article 2; Kyoto Protocol). Thus, forests have to be seen in the framework of the multiple dimensions of sustainable development, if the positive co-benefits from forestry mitigation activities have to be maximized. Important environmental, social, and economic ancillary benefits can be gained by considering forestry mitigation options as an element of the broader land management plans. 9.7.1
9.6.6.5
Conceptual aspects
Options for scaling up
Despite relative low costs and many possible positive sideeffects, the pace with which forest carbon projects are being implemented is slow. This is due to a variety of barriers. Barriers can be categorized as economic, risk-related, political/ bureaucratic, logistic, and capacity or political will (the latter barrier also occurring in industrialized countries; Trines et al., 2006). One of the most important climate-related barriers is the complexity of the rules for afforestation and reforestation project activities. This leads to uncertainty among project developers and investors. Temporary accounting of credits is a major obstacle for two reasons: (1) The future value of temporary CERs depends on the buyer’s confidence in the underlying project. This may limit investor interest in getting involved in project development. (2) The value of temporary CERs hinges on future allowance price expectations because they will have to be replaced in future commitment periods. Furthermore, EU has deferred its decision to accept forestry credits under its emissions trading scheme. Even if EU decided to integrate these credits, this would come too late to take effect in the first commitment period because trees need time to grow. Given the low value of temporary CERs, transaction costs have a higher share in afforestation and reforestation than in energy mitigation projects. Simplified small-scale rules were introduced in order to reduce transaction costs, but the maximum size of 8 kilotonnes of average annual CO2 net removal limits their viability. For forestry mitigation projects to become viable on a larger scale, certainty over future commitments is needed because forestry needs a long planning horizon. Rules need to be streamlined, based on the experience gathered so far. Standardization of project assessment can play important roles
Forestry policies and measures undertaken to reduce GHG emissions may have significant positive or negative impacts on environmental and sustainable development objectives that are a central focus of other multilateral environmental agreements (MEAs), including UN Convention on Biological Diversity (CBD), UN Convention to Combat Desertification (CCD), and Ramsar Convention on Wetlands. In Article 2.1(a, b), Kyoto Protocol, Parties agreed various ways to consider potential impacts of mitigation options and whether and how to establish some common approaches to promoting the sustainable development contributions of forestry measures. In addition, a broad range of issues relating to forest conservation and sustainable forest management have been the focus of recent dialogues under the Intergovernmental Forum on Forests. Recent studies highlighted that strategic thinking about the transition to a sustainable future is particularly important for land (Swanson et al., 2004). In many countries, a variety of separate sets of social, economic and environmental indicators are used, making it difficult to allow for adequate monitoring and analysis of trade-offs between these interlinked dimensions. Still, sustainable development strategies often remain in the periphery of government decision-making processes; and lack coordination between sub-national and local institutions; and economic instruments are often underutilized. To manage forest ecosystems in a sustainable way implies knowledge of their main functions, and the effects of human practices. In recent years, scientific literature has shown an increasing attempt to understand integrated and longterm effects of current practices of forest management on 573
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sustainable development. But often, environmental or socioeconomic effects are considered in isolation, or there is no sufficient understanding of the potential long-term impacts of current practices on sustainable development. Payment for Environmental Services (PES) schemes for forest services (recognizing carbon value) may be foreseen as part of forest management implementation, providing new incentives to change to more sustainable decision patterns. Experience, however, is still fairly limited and is concentrated in a few countries, notably in Latin America, and has had mixed results to date (Wunder, 2004). Important environmental, social, and economic ancillary benefits can be gained by considering forestry mitigation options as an element of the broad land management plans, pursuing sustainable development paths, involving local people and stakeholders and developing adequate policy frameworks. 9.7.2
Ancillary effects of GHG mitigation policies
Climate mitigation policies may have benefits that go beyond global climate protection and actually accrue at the local level (Dudek et al., 2002). Since ancillary benefits tend to be local, rather than global, identifying and accounting for them can reduce or partially compensate the costs of the mitigation measures. However, forests fulfil many important environmental functions and services that can be enhanced or negatively disturbed by human activities and management decisions. Negative effects can be triggered by some mitigation options under certain circumstances. Positive and negative impacts of mitigation options on sustainable development are presented in Table 9.10. Stopping or slowing deforestation and forest degradation (loss of carbon density) and sustainable forest management may significantly contribute to avoided emissions, conserve water resources and prevent flooding, reduce run-off, control erosion, reduce river siltation, and protect fisheries and investments in hydroelectric power facilities; and at the same time, preserve biodiversity (Parrotta, 2002). Thus, avoided deforestation has large positive implications for sustainable development. Further, natural forests are a significant source of livelihoods to hundreds and millions of forest-dependent communities. Plantations provide an option to enhance terrestrial sinks and mitigate climate change. Effects of plantations on sustainable development of rural societies have been diverse, depending on socio-economic and environmental conditions and management regime. Plantations may have either significant positive and /or negative effects (environmental and social effects). They can positively contribute, for example, to employment, economic growth, exports, renewable energy supply and poverty alleviation. In some instances, plantation may also lead to negative social impacts such as loss of grazing land and source of traditional livelihoods.
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Large investments have been made in commercial plantations on degraded lands in Asia. However, lack of consultation with stakeholders (state of land tenure and use rights) may result in failure to achieve the pursued results. Better integration between social goals and afforestation is necessary (Farley et al., 2004). As demand increases for lands to afforest, more comprehensive, multidimensional environmental assessment and planning will be required to manage land sustainably. Agro-forestry can produce a wide range of economic, social and environmental benefits, and probably wider than in case of large-scale afforestation. Agro-forestry systems could be an interesting opportunity for conventional livestock production with low financial returns and negative environmental effects (overgrazing and soil degradation). For many livestock farmers, who may face financial barriers to develop this type of combined systems (e.g., silvo-pastoral systems), payment for environmental services could contribute to the feasibility of these initiatives (Gobbi, 2003). Shadow trees and shelter may have also beneficial effects on livestock production and income, as reported by Bentancourt et al., (2003). Little evidence of local extinctions and invasions of species risking biodiversity has been found when practising agro-forestry (Clavijo et al., 2005). 9.7.3
Implications of mitigation options on water, biodiversity and soil
The Millennium Development Goals (MDGs) aim at poverty reduction, and to improve health, education, gender equality, sanitation and environmental sustainability to promote Sustainable Development. Forest sector can significantly contribute to reducing poverty and improving livelihoods (providing access to forest products such as fuelwood, timber, and non timber products). Land degradation, access to water and food and human health remained at the centre of global attention under the debate on the World Summit on Sustainable Development (WSSD). A focus on five key thematic areas was proposed (Water, Energy, Health, Agriculture, and Biodiversity -WEHAB), driving attention to the fact that managing the natural resources like forest in a sustainable and integrated manner is essential for sustainable development. In this regard, to reverse the current trend in forest degradation as soon as possible, strategies need to be implemented that include targets adopted at national and, where appropriate, regional levels to protect ecosystems and to achieve integrated management of land, water and living resources associated to forest areas, while strengthening regional, national and local capacities. Literature describing in detail the environmental impacts of different forest activities is still scarce and focuses mostly on planted forests. For these reasons, the discussion focuses more on plantations. It is important to underline that while benefits of climate change mitigation are global, co-benefits and costs tend to be local (OECD, 2002) and, in accordance, trade-offs have to be considered at local level.
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Forestry
Table 9.10: Sustainable development implications of forestry mitigation Activity category
Sustainable development implications Social
Economic
Environmental
Positive or negative
Positive
A. Increasing or maintaining the forest area Reducing deforestation and forest degradation
Afforestation/ reforestation
Positive Promotes livelihood.
Provides sustained income for poor communities. Forest protection may reduce local incomes.
Biodiversity conservation. Watershed protection. Soil protection. Amenity values (Nature reserves, etc.)
Positive or negative
Positive or negative
Positive or negative
Promotes livelihood. Slows population migration to other areas (when a less intense land use is replaced). Displacement of people may occur if the former activity is stopped, and alternate activities are not provided. Influx of outside population has impacts on local population.
Creation of employment (when less intense land use is replaced). Increase/decrease of the income of local communities. Provision of forest products (fuelwood, fibre, food construction materials) and other services.
Impacts on biodiversity at the tree, stand, or landscape level depend on the ecological context in which they are found. Potential negative impacts in case on biodiversity conservation (monospecific plantations replacing biodiverse grasslands or shrub lands). Watershed protection (except if waterhungry species are used) . Losses in stream flow. Soil protection. Soil properties might be negatively affected.
Positive
Positive
B. Changing to sustainable forest management Forest Positive management Promotes livelihood. in plantations
Sustainable forest management in native forest
Positive Promotes livelihood.
Creation of employment Increase of the income of local communities. Provision of forest products (fuelwood, fibre, food, construction materials) and other services. Positive Creation of employment. Increase of the income of local communities. Provision of forest products (fuelwood, fibre, food, construction materials) and other services.
Enhance positive impacts and minimize negative implications on biodiversity, water and soils.
Positive Sustainable management prevents forest degradation, conserves biodiversity and protects watersheds and soils.
C. Substitution of energy intensive materials Substitution of fossil intensive products by wood products
Positive or negative
Positive
Forest owners may benefit. Increased local income and employment Potential for competition with the in rural and urban areas. agricultural sector (food production, etc.). Potential diversification of local economies. Reduced imports.
Negative Non-sustainable harvest may lead to loss of forests, biodiversity and soil.
D. Bioenergy Bioenergy production from forestry
Positive or negative
Positive or negative
Forest owners may benefit. Potential for competition with the agricultural sector (food production, etc.)
Increased local income and employment. Potential diversification of local economies. Provision of renewable and independent energy source. Potential competition with the agricultural sector (food production, etc.)
Positive or negative Benefits if production of fuelwood is done in a sustainable way. Mono specific short rotation plantations for energy may negatively affect biodiversity, water and soils, depending on site conditions.
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Water cycle: Afforestation may result in better balance in the regional water cycle balance by reducing run-off, flooding, and control of groundwater recharge and watersheds protection. However, massive afforestation grasslands may reduce water flow into other ecosystems and rivers, and affect aquifers layer and recharge, and lead to substantial losses in stream flow (Jackson et al, 2005). In addition, some possible changes in soil properties are largely driven by changes in hydrology. Soils: Intensively managed plantations have nutrient demands that may affect soil fertility and soil properties, for example leading to higher erosion of the uncovered mineral soil surface (Perez-Bidegain et al., 2001; Carrasco-Letellier et al., 2004); and biological properties changes (Sicardi et al., 2004) if the choice of species is not properly matched with site conditions. Regarding chemical properties, increased Na concentrations, exchangeable sodium percentage and soil acidity, and decreased base saturation have been detected in many situations. (Jackson, et al., 2005).In general, afforestation of low soil carbon croplands may present considerable opportunities for carbon sequestration in soil, while afforestation of grazing land can result in relatively smaller increases or decreases in soil carbon (Section 9.4.2.2). Most mitigation options other than monoculture plantations conserve and protect soils and watersheds. Biodiversity: Plantations can negatively affect biodiversity if they replace biologically rich native grassland or wetland habitats (Wagner, et al., 2006). Also, plantations can have either positive or negative impacts on biodiversity depending on management practices (Quine and Humphrey, 2005). Plantations may act as corridors, source, or barriers for different species, and a tool for landscape restoration (Parrota, 2002). Other forestry mitigation options such as reducing deforestation, agro-forestry, multi-species plantations, and sustainable native forest management lead to biodiversity conservation. Managing plantations to produce goods (such as timber) while also enhancing ecological services (such as biodiversity) involves several trade-offs. Overcoming them involves a clear understanding of the broader ecological context in which plantations are established as well as participation of the different stakeholders. The primary management objective of most industrial plantations traditionally has been to optimize timber production. This is not usually the case in small-scale plantations owned by farmers, where more weight is given to non-timber products and ecological services. A shift from a stand level to a broader forest and non-forest landscape level approach will be required to achieve a balance between biodiversity and productivity/profitability. The literature seems to suggest that plantations, mainly industrial plantations, require careful assessment of the potential impacts on soils, hydrological cycle and biodiversity, and that negative impacts could be controlled or minimized if adequate landscape planning and basin management and good practices are introduced. Carbon sequestration strategies 576
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with afforestation of non-forest lands should consider their full environmental consequences. The ultimate balance of cobenefits and impacts depends on the specific site conditions and previous and future land and forest management.
9.8 Technology, R&D, deployment, diffusion and transfer R&D and technology transfer have a potential to promote forest sector mitigation options by increasing sustainable productivity, conserving biodiversity and enhancing profitability. Technologies are available for promoting mitigation options from national level to forest stand level, and from single forest practices to broader socio-economic approaches (IPCC, 2000b). Traditional and/or existing techniques in forestry including planting, regeneration, thinning and harvesting are fundamental for implementation of mitigation options such as afforestation, reforestation, and forest management. Further, improvement of such sustainable techniques is required and transfer could build capacity in developing countries. Biotechnology may have an important role especially for afforestation and reforestation. As the area of planted forests including plantations of fast-growing species for carbon sequestration increases, sustainable forestry practices will become more important for both productivity and environment conservation. The development of suitable low-cost technologies will be necessary for promoting thinning and mitigation options. Moreover, technology will have to be developed for making effective use of small wood, including thinned timber, in forest products and markets. Thinning and tree pruning for fuelwood and fodder are regularly conducted in many developing countries as part of local integrated forest management strategies. Although natural dynamics are part of the forest ecosystem, suppression of forest fires and prevention of insect and pest disease are important for mitigation. Regarding technology for harvesting and procurement, mechanized forest machines such as harvesters, processors and forwarders developed in Northern Europe and North America have been used around the world for the past few decades. Mechanization under sustainable forest management seems to be effective for promoting mitigation options including product and energy substitution (Karjalainen and Asikainen, 1996). However, harvesting and procurement systems vary due to terrain, type of forest, infrastructure and transport regulations, and appropriate systems also vary by regions and countries. Reduced impact logging is considered in some cases such as in tropical forests (Enters et al., 2002). There is a wide array of technologies for using biomass from plantations for direct combustion, gasification, pyrolysis,
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and fermentation (see Section 4.3.3.3). To conserve forest resources, recycling of wood waste material needs to be expanded. Technology for manufacturing waste-derived board has almost been established, but further R&D will be necessary to re-use waste sawn timber, or to recycle it as lumber. While these technologies often need large infrastructure and incentives in industrialized countries, practical devices such as new generations of efficient wood-burning cooking stoves (Masera et al., 2005) have proved effective in developing countries. They are effective as a means to reduce the use of wood fuels derived from forests, at the same time providing tangible sustainable development benefits for local people, such as reduction in indoor air pollution levels. Technological R&D for estimation of carbon stocks and fluxes is fundamental not only for monitoring but also for evaluating policies. Practical methods for estimating carbon stocks and fluxes based on forest inventories and remote sensing have been recommended in the Good Practice Guidance for LULUCF (IPCC, 2003). Over the last three decades, earth observation satellites have increased in number and sophistication (DeFries et al., 2006). High-resolution satellite images have become available, so new research on remote sensing has begun on using satellite radar and LIDAR (light detection and ranging) for estimating forest biomass (Hirata et al., 2003). Remote sensing methods are expected to play an increasing role in future assessments, especially as a tool for mapping land cover and its change over time. However, converting these maps into estimates of carbon sources and sinks remains a challenge and will continue to depend on in-situ measurements and modelling. Large-scale estimations of the forest sector and its carbon balance have been carried out with models such as the CBMCFS2 (Kurz and Apps, 2006), CO2FIX V.2 model (Masera et al., 2003), EFISCEN (Nabuurs et al., 2005, 2006), Full CAM (Richards and Evans, 2004), and GORCAM (Schlamadinger and Marland, 1996). Micrometeorological observation of carbon dioxide exchange between the terrestrial ecosystem and the atmosphere has been carried out in various countries (Ohtani, 2005). Based on the observation, a global network FLUXNET (Baldocchi et al., 2001) and regional networks including AmeriFlux, EUROFLUX, AsiaFlux and OzNet are being enlarged for stronger relationships. New technologies for monitoring and verification including remote sensing, carbon flux modelling, micrometeorological observation and socio-economic approaches described above will facilitate the implementation of mitigation options. Furthermore, the integration of scientific knowledge, practical techniques, socio-economic and political approaches will become increasingly significant for mitigation technologies in the forest sector.
Forestry
Few forest-based mitigation analyses have been conducted using primary data. There is still limited insight regarding impacts on soils, lack of integrated views on the many sitespecific studies, hardly any integration with climate impact studies, and limited views in relation to social issues and sustainable development. Little new effort was reported on the development of global baseline scenarios of land-use change and their associated carbon balance, against which mitigation options could be examined. There is limited quantitative information on the cost-benefit ratios of mitigation interventions. Technology deployment, diffusion and transfer in the forestry sector provide a significant opportunity to help mitigate climate change and adapt to potential changes in the climate. Apart from reducing GHG emissions or enhancing the carbon sinks, technology transfer strategies in the forest sector have the potential to provide tangible socio-economic and local and global environmental benefits, contributing to sustainable development (IPCC, 2000b). Especially, technologies for improving productivity, sustainable forest management, monitoring, and verification are required in developing countries. However, existing financial and institutional mechanism, information and technical capacity are inadequate. Thus, new policies, measures and institutions are required to promote technology transfer in the forest sector. For technology deployment, diffusion and transfer, governments could play a critical role in: a) providing targeted financial and technical support through multilateral agencies (World Bank, FAO, UNDP, UNEP), in developing and enforcing the regulations to implement mitigation options; b) promoting the participation of communities, institutions and NGOs in forestry projects; and c) creating conditions to enable the participation of industry and farmers with adequate guidelines to ensure forest management and practices as mitigation options. In addition, the role of private sector funding of projects needs to be promoted under the new initiatives, including the proposed flexible mechanisms under the Kyoto Protocol. The Global Environmental Facility (GEF) could fund projects that actively promote technology transfer and capacity building in addition to the mitigation aspects (IPCC, 2000b).
9.9
Long-term outlook
Mitigation measures up to 2030 can prevent the biosphere going into a net source globally. The longer-term mitigation prospects (beyond 2030) within the forestry sector will be influenced by the interrelationship of a complex set of environmental, socio-economic and political factors. The history of land-use and forest management processes in the last century, particularly within the temperate and boreal regions, as well as on the recent patterns of land-use will have a critical effect on the mitigation potential. Several studies have shown that uncertainties in the contemporary carbon cycle, the uncertain future impacts of 577
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climatic change and its many dynamic feedbacks can cause large variation in future carbon balance projections (Lewis et al., 2005). Other scenarios suggest that net deforestation pressure will slow over time as population growth slows and crop and livestock productivity increase. Despite continued projected loss of forest area, carbon uptake from afforestation and reforestation could result in net sequestration (Section 3.2.2). Also, the impacts of climate change on forests will be a major source of uncertainty regarding future projections (Viner et al., 2006). Other issues that will have an effect on the longterm mitigation potential include future sectoral changes within forestry, changes in other economic sectors, as well as political and social change, and the particular development paths within industrialized and developing countries beyond the first half of the 21st century. The actual mitigation potential will depend ultimately on solving structural problems linked to the sustainable management of forests. Such structural problems include securing land tenure and land rights of indigenous people, reducing poverty levels in rural areas and the rural-urban divide, and providing disincentives to short-term behaviour of economic actors and others. Considering that forests store more carbon dioxide than the entire atmosphere (Stern, 2006), the role of forests is critical. Forestry mitigation projections are expected to be regionally unique, while still linked across time and space by changes in global physical and economic forces. Overall, it is expected that boreal primary forests will either be sources or sinks depending on the net effect of some enhancement of growth due to climate change versus a loss of soil organic matter and emissions from increased fires. The temperate forests in USA, Europe, China and Oceania, will probably continue to be net carbon sinks, favoured also by enhanced forest growth due to climate change. In the tropical regions, the human induced land-use changes are expected to continue to drive the dynamics for decades. In the meantime, the enhanced growth of large areas of primary forests, secondary regrowth, and increasing plantation areas will also increase the sink. Beyond 2040, depending on the extent and effectiveness of forest mitigation activities within tropical areas, and very particularly on the effectiveness of policies aimed at reducing forest degradation and deforestation, tropical forest may become net sinks. In the medium to long term as well, commercial bio-energy is expected to become increasingly important. In the long-term, carbon will only be one of the goals that drive land-use decisions. Within each region, local solutions have to be found that optimize all goals and aim at integrated and sustainable land use. Developing the optimum regional strategies for climate change mitigation involving forests will require complex analyses of the trade-offs (synergies and competition) in land-use between forestry and other land uses,
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the trade-offs between forest conservation for carbon storage and other environmental services such as biodiversity and watershed conservation and sustainable forest harvesting to provide society with carbon-containing fibre, timber and bioenergy resources, and the trade-offs among utilization strategies of harvested wood products aimed at maximizing storage in long-lived products, recycling, and use for bioenergy.
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